Posted Updated Agent Skills / Cloud & Operations2 hours read (About 17928 words)

Cloud & Operations | Agent Skills

Cloud & Operations

Cloud and operations skills address deployment, infrastructure, observability, reliability, and cloud-service configuration.

Catalog snapshot: November 2, 2026

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Skills in this category

AceDataCloud/fish-audio

Catalog entry: Specialized Domains
Source documentation: https://github.com/AceDataCloud/Skills/blob/main/skills/fish-audio/SKILL.md

Function: Generate speech and clone voices with Fish Audio

When to use it: Use when a task needs the capability described in this catalog entry: Generate speech and clone voices with Fish Audio

The catalog does not state a separate trigger condition. This usage note is inferred from the published function description.

Source skill menu:

  • Fish Audio — Text-to-Speech
  • First-time setup
  • Quick Start
  • Endpoints
  • Workflows
  • 1. Find a reference voice
  • 2. Text-to-Speech
  • 3. One-shot voice cloning
  • 4. Async TTS
  • 5. Create a persistent public voice model
  • 6. List voices created by the calling account
  • Parameters — `/fish/tts`
  • Header
  • JSON body
  • Gotchas

browserbase/functions

Catalog entry: Skills by Browserbase
Source documentation: https://github.com/browserbase/skills/blob/main/skills/functions/SKILL.md

Function: Deploy browser automation scripts as serverless cloud functions

When to use it: Use when the user wants to deploy browser automation to run on a schedule or cron, create a webhook endpoint for browser tasks, run automation in the cloud instead of locally, or asks about Browserbase Functions.

Usage guidance is taken from the skill’s own trigger description or usage section.

Source skill menu:

  • Browserbase Functions
  • Prerequisites
  • Creating a Function Project
  • 1. Initialize
  • 2. Add Credentials to .env
  • 3. Install Dependencies
  • Function Structure
  • Development Workflow
  • 1. Start Dev Server
  • 2. Test Locally
  • 3. Iterate
  • Deploying
  • Quick Reference

clickhouse/chdb-sql

Catalog entry: Skills by ClickHouse
Source documentation: https://github.com/clickhouse/agent-skills/blob/main/skills/chdb-sql/SKILL.md

Function: In-process ClickHouse SQL engine for Python — query files, databases, and cloud storage without a server

When to use it: Use when the user wants to run SQL — especially analytical SQL — on local files (parquet/csv/json), URLs, S3 paths, or remote databases (Postgres, MySQL, MongoDB, ClickHouse Cloud, Iceberg, Delta Lake) without setting up a server. Provides chDB — embedded ClickHouse SQL in Python with 1000+ functions, Session for stateful multi-step pipelines, parametrized queries, and cross-source joins via `s3()`, `mysql()`, `postgresql()`, `iceberg()`, `deltaLake()`, `remoteSecure()` table functions. TRIGGER when: user wants SQL on parquet/csv/files or across remote analytical sources; uses ClickHouse SQL features (window func

Usage guidance is taken from the skill’s own trigger description or usage section.

Source skill menu:

  • chdb SQL — ClickHouse in Your Python Process
  • Decision Tree: Pick the Right API
  • chdb.query() — One Line, Any Data
  • Session — Stateful Analysis Pipelines
  • Connection API (DB-API 2.0)
  • Troubleshooting
  • References

clickhouse/clickhousectl-cloud-deploy

Catalog entry: Skills by ClickHouse
Source documentation: https://github.com/clickhouse/agent-skills/blob/main/README.md

Function: Deploy to ClickHouse Cloud and migrate from local setups with clickhousectl

When to use it: Taking a local ClickHouse prototype into production on ClickHouse Cloud Provisioning a managed ClickHouse service with clickhousectl Migrating schemas and data from a local instance to ClickHouse Cloud Setting up cloud-hosted ClickHouse for an application team Standardizing cloud deployment steps across multiple environments

Usage guidance is taken from the skill’s own trigger description or usage section.

Source skill menu:

  • ClickHouse Agent Skills
  • Installation
  • npx
  • clickhousectl
  • What is this?
  • Available Skills
  • ClickHouse Best Practices
  • ClickHouse Architecture Advisor
  • ClickHouse JS Node Troubleshooting
  • chdb DataStore
  • chdb SQL
  • Infra ClickHouse
  • Infra Postgres
  • ClickStack OTel Collector
  • Quick Start
  • Supported Agents

CloudAI-X/threejs-skills

Catalog entry: Development and Testing
Source documentation: https://github.com/CloudAI-X/threejs-skills/blob/main/README.md

Function: Three.js skills for creating 3D elements and interactive experiences

When to use it: Use when a task needs the capability described in this catalog entry: Three.js skills for creating 3D elements and interactive experiences

The catalog does not state a separate trigger condition. This usage note is inferred from the published function description.

Source skill menu:

  • Three.js Skills for Claude Code
  • Why
  • Installation
  • Skills Included
  • How It Works
  • Skill File Structure
  • Verification
  • License
  • Acknowledgments

This catalog entry points to a collection. The scanned repository lists 13 distinct skill-file paths.

Sample members: threejs-animation · threejs-asset-pipeline · threejs-fundamentals · threejs-geometry · threejs-interaction · threejs-lighting · threejs-loaders · threejs-materials
More members are available in the source repository.

cloudflare/agents-sdk

Catalog entry: Skills by Cloudflare Team
Source documentation: https://github.com/cloudflare/skills/blob/main/skills/agents-sdk/SKILL.md

Function: Build stateful AI agents with scheduling, RPC, and MCP servers

When to use it: Running scheduled cron tasks inside a Cloudflare Worker agent Building a chat app where agent state syncs in real time to React clients Wiring up an MCP server using McpAgent to expose callable tools Handling inbound emails and sending replies through an agent’s routing logic Pausing a multi-step workflow until a human approves the next action

Usage guidance is taken from the skill’s own trigger description or usage section.

Source skill menu:

  • Cloudflare Agents SDK
  • Retrieval Sources
  • Capabilities
  • FIRST: Verify Installation
  • Wrangler Configuration
  • Agent Class
  • Routing
  • Core APIs
  • React Client
  • References
  • Core
  • Chat & Streaming
  • Background Processing
  • Integrations
  • Experimental
  • Skill feedback

cloudflare/cloudflare

Catalog entry: Skills by Cloudflare Team
Source documentation: https://github.com/cloudflare/skills/blob/main/skills/cloudflare/SKILL.md

Function: Comprehensive Cloudflare platform skill covering Workers, Pages, storage, AI, networking, security, and IaC

When to use it: Picking the right Cloudflare primitives (Workers, Pages, D1, R2, Durable Objects) for a new project Wiring up Workers AI or Vectorize into an existing application Standing up a Cloudflare Tunnel or Spectrum listener for an internal service Configuring WAF and DDoS protections for a production domain Managing Cloudflare resources as code via Terraform or Pulumi

Usage guidance is taken from the skill’s own trigger description or usage section.

Source skill menu:

  • Discover and build with Cloudflare
  • Choose the CLI
  • Help the user find the right product
  • What are you trying to build?
  • Find guidance for a task not listed here
  • Caching
  • Working principles
  • Skill feedback

cloudflare/cloudflare-email-service

Catalog entry: Skills by Cloudflare Team
Source documentation: https://github.com/cloudflare/skills/blob/main/skills/cloudflare-email-service/SKILL.md

Function: Send transactional email and route inbound mail with Cloudflare Email Sending and Email Routing

When to use it: Adding transactional email sending to a Cloudflare Worker via a binding Routing inbound email for a domain to a Worker for processing Sending email from a Node.js or Python app via the REST API Wiring email handling into an Agents SDK agent Configuring SPF, DKIM, and DMARC for a new sending domain

Usage guidance is taken from the skill’s own trigger description or usage section.

Source skill menu:

  • Cloudflare Email Service
  • Retrieval Sources
  • FIRST: Check Prerequisites
  • What Do You Need?
  • Sending Workflow
  • Common Mistakes
  • References
  • Skill feedback

cloudflare/durable-objects

Catalog entry: Skills by Cloudflare Team
Source documentation: https://github.com/cloudflare/skills/blob/main/skills/durable-objects/SKILL.md

Function: Stateful coordination with RPC, SQLite, and WebSockets

When to use it: Building a multiplayer game room where turn order and scores must stay consistent across players Coordinating a booking system so two users cannot reserve the same slot simultaneously Managing per-tenant SQLite storage in a multi-tenant SaaS app without a separate database Scheduling per-entity alarms for things like subscription renewal reminders or session timeouts Handling persistent WebSocket connections for a live collaboration tool with shared document state

Usage guidance is taken from the skill’s own trigger description or usage section.

Source skill menu:

  • Durable Objects
  • Retrieval Sources
  • When to Use
  • Reference Documentation
  • Core Principles
  • Use Durable Objects For
  • Do NOT Use For
  • Quick Reference
  • Wrangler Configuration
  • Basic Durable Object Pattern
  • Critical Rules
  • Authorization
  • Anti-Patterns (NEVER)
  • Stub Creation
  • Storage Operations
  • Alarms

cloudflare/sandbox-sdk

Catalog entry: Skills by Cloudflare Team
Source documentation: https://github.com/cloudflare/skills/blob/main/README.md

Function: Build sandboxed applications for secure, isolated code execution on Workers

When to use it: Running untrusted user-submitted code from an AI code interpreter Building a web-based coding playground with isolated execution Executing CI/CD test steps in an isolated sandbox per run Spinning up interactive dev environments with preview URLs Running tool-call code for an agent without exposing the host Worker

Usage guidance is taken from the skill’s own trigger description or usage section.

Source skill menu:

  • Cloudflare Skills
  • Installing
  • Codex
  • Claude Code
  • VS Code / GitHub Copilot
  • Cursor
  • npx skills
  • Clone / Copy
  • Skills
  • MCP Servers

cloudflare/security-audit-skill

Catalog entry: Skills by Cloudflare Team
Source documentation: https://github.com/cloudflare/security-audit-skill/blob/main/skills/security-audit/SKILL.md

Function: Multi-phase security audits with independently verified, machine-readable findings

When to use it: Use when a task needs the capability described in this catalog entry: Multi-phase security audits with independently verified, machine-readable findings

The catalog does not state a separate trigger condition. This usage note is inferred from the published function description.

Source skill menu:

  • Security Audit
  • Operating modes
  • Platform terminology
  • Universal execution safety
  • Full audit setup
  • Write isolation
  • Full audit planning
  • Coverage and prior runs
  • Run profiles and scope
  • Core principles
  • Require a boundary and result
  • Use bounded local evidence
  • Respect source visibility
  • Separate priority from certainty
  • Recommend the smallest effective source fix
  • Full audit workflow

cloudflare/web-perf

Catalog entry: Skills by Cloudflare Team
Source documentation: https://github.com/cloudflare/skills/blob/main/skills/web-perf/SKILL.md

Function: Audit Core Web Vitals and render-blocking resources

When to use it: Diagnosing why LCP is above 4s on a landing page Tracing which CSS or JS files are blocking first paint Finding images missing width/height attributes that cause layout shifts Checking cache headers and compression on static assets Auditing a Next.js or Vite app’s bundle for unused code and oversized polyfills

Usage guidance is taken from the skill’s own trigger description or usage section.

Source skill menu:

  • Web Performance Audit
  • Retrieval Sources
  • FIRST: Verify MCP Tools Available
  • Key Guidelines
  • Quick Reference
  • Workflow
  • Phase 1: Performance Trace
  • Phase 2: Core Web Vitals Analysis
  • Phase 3: Network Analysis
  • Phase 4: Accessibility Snapshot
  • Phase 5: Codebase Analysis
  • Detect Framework & Bundler
  • Tree-Shaking & Dead Code
  • Unused JS/CSS
  • Polyfills
  • Compression & Minification

cloudflare/workers-best-practices

Catalog entry: Skills by Cloudflare Team
Source documentation: https://github.com/cloudflare/skills/blob/main/skills/workers-best-practices/SKILL.md

Function: Review and author Workers code against production best practices and wrangler.jsonc conventions

When to use it: Use when writing, reviewing, or configuring Workers.

Usage guidance is taken from the skill’s own trigger description or usage section.

Source skill menu:

  • References
  • Keep Compatibility Dates Current
  • Enable Observability
  • Place Compute Near Regional Databases
  • Anti-Patterns to Flag
  • Validation
  • Scope
  • Skill feedback

cloudflare/wrangler

Catalog entry: Skills by Cloudflare Team
Source documentation: https://github.com/cloudflare/skills/blob/main/skills/wrangler/SKILL.md

Function: Deploy and manage Workers, KV, R2, D1, Vectorize, Queues, Workflows

When to use it: Deploying a Worker to staging and production environments from a single config file Running D1 SQL migrations against a remote database before a release Streaming live error logs from a production Worker with filtered output Rolling back a Worker deployment to a specific previous version Seeding a KV namespace with bulk data from a local JSON file

Usage guidance is taken from the skill’s own trigger description or usage section.

Source skill menu:

  • Wrangler CLI
  • Inspect the Project
  • Retrieve What the Task Needs
  • Apply the Change
  • Work with Workers Previews
  • Validate
  • Skill feedback

crawlbase/storage-bulk-delete

Catalog entry: Skills by Crawlbase
Source documentation: https://github.com/crawlbase/crawlbase-codex-plugin/blob/main/skills/storage-bulk-delete/SKILL.md

Function: Delete up to 100 stored pages from Crawlbase Cloud Storage in one call

When to use it: Clearing out a batch of processed crawl results in one call Emptying the JS-token silo after a screenshot-heavy job Enforcing retention by deleting rids older than a cutoff Combining with storage-list to wipe a token’s storage completely

Usage guidance is taken from the skill’s own trigger description or usage section.

Source skill menu:

  • When to use
  • Usage
  • Example prompts

crawlbase/storage-count

Catalog entry: Skills by Crawlbase
Source documentation: https://github.com/crawlbase/crawlbase-codex-plugin/blob/main/skills/storage-count/SKILL.md

Function: Count the documents held in Crawlbase Cloud Storage for a token

When to use it: Checking storage usage before running bulk operations Answering “how many pages have we stored?” at a glance Verifying that a batch of store: true crawls actually landed Counting the JS-token silo separately from the normal one

Usage guidance is taken from the skill’s own trigger description or usage section.

Source skill menu:

  • When to use
  • Usage
  • Example prompts

crawlbase/storage-delete

Catalog entry: Skills by Crawlbase
Source documentation: https://github.com/crawlbase/crawlbase-codex-plugin/blob/main/skills/storage-delete/SKILL.md

Function: Delete a single stored page from Crawlbase Cloud Storage by rid

When to use it: Removing a specific stored page that is no longer needed Deleting a stored screenshot page from the JS-token silo Cleaning up a single failed or outdated crawl result

Usage guidance is taken from the skill’s own trigger description or usage section.

Source skill menu:

  • When to use
  • Usage
  • Example prompts

crawlbase/storage-get

Catalog entry: Skills by Crawlbase
Source documentation: https://github.com/crawlbase/crawlbase-codex-plugin/blob/main/skills/storage-get/SKILL.md

Function: Retrieve a stored page from Crawlbase Cloud Storage as JSON, HTML, or Markdown

When to use it: Re-reading a crawled page later without spending another crawl request Converting a stored HTML page to Markdown for summarization Retrieving a JS-rendered page stored under the JS token silo Looking up a stored page by its original URL when the rid is unknown

Usage guidance is taken from the skill’s own trigger description or usage section.

Source skill menu:

  • When to use
  • Usage
  • Example prompts

d1vai/d1v

Catalog entry: Development and Testing
Source documentation: https://github.com/d1vai/d1v-cli/blob/main/skills/d1v/SKILL.md

Function: Deploy web projects with verified previews and confirmed production releases

When to use it: Use when a task involves D1V authentication, project binding, workspace synchronization, container commands, environment metadata, preview deployments, deployment status, or a user-confirmed production release.

Usage guidance is taken from the skill’s own trigger description or usage section.

Source skill menu:

  • d1v CLI
  • Safety
  • Authenticate and discover
  • Bind a local workspace
  • Run commands in a workspace
  • Environment metadata
  • Deployments
  • Local runtime
  • References

datadog-labs/dd-monitors

Catalog entry: Skills by Datadog Labs
Source documentation: https://github.com/datadog-labs/agent-skills/blob/main/dd-monitors/SKILL.md

Function: Manage Datadog monitors through the pup CLI

When to use it: Creating a new metric alert from a JSON file with proper thresholds Auditing monitors to find ones missing team ownership tags Listing all monitors filtered by a specific team or service tag Scheduling a downtime window before a planned deployment Checking which monitors are flapping and tightening their evaluation windows

Usage guidance is taken from the skill’s own trigger description or usage section.

Source skill menu:

  • Datadog Monitors
  • Prerequisites
  • Command Execution Order (Token-Efficient)
  • Quick Start
  • Common Operations
  • List Monitors
  • Get Monitor
  • Create Monitor
  • Silence Alerts (Downtime)
  • Monitor Creation Best Practices
  • 1. Avoid Alert Fatigue
  • 2. Use Proper Scoping
  • 3. Set Recovery Thresholds
  • 4. Include Context in Messages
  • NEVER Delete Monitors Directly
  • Monitor Types

expo/expo-cicd-workflows

Catalog entry: Skills by Expo Team
Source documentation: https://github.com/expo/skills/blob/main/README.md

Function: CI/CD workflows for Expo projects

When to use it: Writing a new EAS workflow YAML from scratch for a React Native app Adding a deployment step that runs only after a successful build job Configuring workflow triggers for push events or manual dispatch Debugging a workflow that fails schema validation with cryptic errors Setting up parallel build jobs for iOS and Android in a single workflow file

Usage guidance is taken from the skill’s own trigger description or usage section.

Source skill menu:

  • How It Works
  • Installation
  • Skills CLI
  • Claude Code Plugin
  • Codex Plugin
  • Updating
  • Try It
  • Skills Included
  • Start Here
  • Framework (open source)
  • Services & paid distribution
  • Experimental
  • Expo MCP Server
  • FAQ
  • Which AI coding agents are supported?
  • Should I install the skills or the plugin?

expo/expo-deployment

Catalog entry: Skills by Expo Team
Source documentation: https://github.com/expo/skills/blob/main/README.md

Function: Deploy Expo apps to production

When to use it: Submitting an iOS build to TestFlight for beta review Running automated Play Store deployments when code merges to main Generating preview URLs for web app pull requests Managing build version numbers remotely across iOS and Android Setting up a single eas.json config to handle both platform builds and submissions

Usage guidance is taken from the skill’s own trigger description or usage section.

Source skill menu:

  • How It Works
  • Installation
  • Skills CLI
  • Claude Code Plugin
  • Codex Plugin
  • Updating
  • Try It
  • Skills Included
  • Start Here
  • Framework (open source)
  • Services & paid distribution
  • Experimental
  • Expo MCP Server
  • FAQ
  • Which AI coding agents are supported?
  • Should I install the skills or the plugin?

expo/native-data-fetching

Catalog entry: Skills by Expo Team
Source documentation: https://github.com/expo/skills/blob/main/README.md

Function: Network requests, API calls, caching, and offline support

When to use it: Setting up React Query with staleTime and retry config for an Expo app Storing and refreshing auth tokens using expo-secure-store Pausing and resuming queries automatically when the device goes offline Configuring separate API base URLs for development and production builds Cancelling in-flight fetch requests when a component unmounts

Usage guidance is taken from the skill’s own trigger description or usage section.

Source skill menu:

  • How It Works
  • Installation
  • Skills CLI
  • Claude Code Plugin
  • Codex Plugin
  • Updating
  • Try It
  • Skills Included
  • Start Here
  • Framework (open source)
  • Services & paid distribution
  • Experimental
  • Expo MCP Server
  • FAQ
  • Which AI coding agents are supported?
  • Should I install the skills or the plugin?

firebase/firebase-app-hosting-basics

Catalog entry: Skills by Firebase
Source documentation: https://github.com/firebase/agent-skills/blob/main/skills/firebase-app-hosting-basics/SKILL.md

Function: Deploy and manage full-stack web apps (Next.js, Angular, etc.)

When to use it: Use when deploying Next.js/Angular apps, configuring apphosting.yaml or firebase.json apphosting blocks, managing secrets, setting up GitHub CI/CD, or configuring Blaze billing requirements. Don’t use for classic static web hosting, Auth, Firestore, Crashlytics, or Xcode.

Usage guidance is taken from the skill’s own trigger description or usage section.

Source skill menu:

  • App Hosting Basics
  • Description
  • Hosting vs App Hosting
  • Deploying to App Hosting
  • Deploy from Source
  • Automated deployment via GitHub (CI/CD)
  • Emulation

firebase/firebase-data-connect-basics

Catalog entry: Skills by Firebase
Source documentation: https://github.com/firebase/agent-skills/blob/main/skills/firebase-data-connect-basics/SKILL.md

Function: Build Firebase Data Connect backends backed by Cloud SQL

When to use it: Use when designing schemas with tables and relations, writing authorized queries and mutations, configuring real-time data updates, or generating type-safe SDKs. Use when you need a relational database with Firebase, or when the user mentions SQL Connect or Data Connect.

Usage guidance is taken from the skill’s own trigger description or usage section.

Source skill menu:

  • Firebase SQL Connect
  • Project Structure
  • Key Tools for Validation
  • Operation Strategies: GraphQL vs. Native SQL
  • Development Workflow
  • 1. Define Data Model (`schema/schema.gql`)
  • 2. Define Authorized Operations (`connector/queries.gql`, `connector/mutations.gql`)
  • 3. Use type-safe SDK in your apps
  • Feature Capability Map
  • Deployment & CLI
  • How to initialize SQL Connect in a Firebase project
  • How to build apps using SQL Connect locally
  • How to deploy SQL Connect to Cloud SQL
  • Examples

firebase/firebase-firestore-standard

Catalog entry: Skills by Firebase
Source documentation: https://github.com/firebase/agent-skills/blob/main/README.md

Function: Complete guide for Cloud Firestore Standard Edition

When to use it: Setting up a new Firestore database for a Firebase project Writing security rules that restrict read/write access by user role Querying Firestore collections from a web app using the modular SDK Creating composite indexes for multi-field queries Deploying updated security rules to a production Firestore instance

Usage guidance is taken from the skill’s own trigger description or usage section.

Source skill menu:

  • Installation
  • Option 1: Agent Skills CLI
  • Option 2: Gemini CLI Extension
  • Option 3: Claude Plugin
  • Option 4: Codex Plugin
  • Option 5: Kimi Plugin
  • Option 6: Manual Set Up
  • Option 7: Local Path via Agent Skills CLI
  • Option 8: Local Development (Live Symlinking)
  • 🤝 Contributing
  • 📄 License

firebase/firebase-hosting-basics

Catalog entry: Skills by Firebase
Source documentation: https://github.com/firebase/agent-skills/blob/main/skills/firebase-hosting-basics/SKILL.md

Function: Deploy static sites, SPAs, and microservices to Firebase Hosting

When to use it: Use when deploying static sites/SPAs, setting up custom domains, configuring firebase.json hosting settings (redirects, rewrites, headers, multi-site), or managing preview channels. Don’t use for Firebase App Hosting (Next.js/SSR), Auth, Firestore queries/rules, Data Connect, or Crashlytics.

Usage guidance is taken from the skill’s own trigger description or usage section.

Source skill menu:

  • hosting-basics
  • Overview
  • Hosting vs App Hosting
  • Instructions
  • 1. Configuration (`firebase.json`)
  • 2. Deploying
  • 3. Emulation

garrytan/land-and-deploy

Catalog entry: Skills by Garry Tan (gstack)
Source documentation: https://github.com/garrytan/gstack/blob/main/land-and-deploy/SKILL.md

Function: Merge the PR, wait for CI and deploy, verify production health

When to use it: Merging a PR and watching the GitHub Actions deploy workflow complete Catching a broken production deploy before users notice Running pre-merge readiness checks on reviews, tests, and changelog updates Verifying a Vercel or Fly.io app loaded correctly after a push Rolling back a bad merge with a revert commit when canary checks fail

Usage guidance is taken from the skill’s own trigger description or usage section.

Source skill menu:

  • Shared preamble (load first)
  • Preamble (run first)
  • Question Tuning (skip entirely if `QUESTION_TUNING: false`)
  • Repo Ownership — See Something, Say Something
  • Search Before Building
  • Telemetry (run last)
  • Step 0: Detect platform and base branch
  • /land-and-deploy — Merge, Deploy, Verify
  • User-invocable
  • Arguments
  • Automation and approval
  • Voice & Tone
  • Section index — Read each section when its situation applies
  • Step 1: Pre-flight
  • Step 1.5: First-run dry-run validation
  • Step 2: Pre-merge checks

garrytan/setup-deploy

Catalog entry: Skills by Garry Tan (gstack)
Source documentation: https://github.com/garrytan/gstack/blob/main/setup-deploy/SKILL.md

Function: Deploy Configurator: one-time setup for /land-and-deploy

When to use it: Setting up /land-and-deploy for the first time on a Fly.io project Reconfiguring deploy settings after switching from Render to Vercel Adding a health check URL to an existing project that deploys via GitHub Actions Configuring post-merge deploy verification for a monorepo with a custom deploy script Updating the production URL after moving a Render app to a custom domain

Usage guidance is taken from the skill’s own trigger description or usage section.

Source skill menu:

  • Shared preamble (load first)
  • Preamble (run first)
  • Question Tuning (skip entirely if `QUESTION_TUNING: false`)
  • Telemetry (run last)
  • Third-Party Web Actions
  • /setup-deploy — Configure Deployment for gstack
  • Instructions
  • Step 1: Check existing configuration
  • Step 2: Detect platform
  • Step 3: Platform-specific setup
  • Step 4: Write configuration
  • Step 5: Verify
  • Step 6: Summary
  • Important Rules

getsentry/sentry-cloudflare-sdk

Catalog entry: Skills by Sentry team for their dev team.
Source documentation: https://github.com/getsentry/sentry-for-ai/blob/main/README.md

Function: Full Sentry SDK setup for Cloudflare Workers, Pages, Durable Objects, Queues, and Workflows

When to use it: Adding @sentry/cloudflare to a Hono-based Worker Instrumenting a Durable Object class with tracing Monitoring a Queue consumer Worker for errors Wiring Sentry into a Cloudflare Pages Functions app Enabling AI monitoring on a Workers-based LLM proxy

Usage guidance is taken from the skill’s own trigger description or usage section.

Source skill menu:

  • Sentry for AI
  • What You Can Do
  • Distribution
  • Build it yourself
  • Skills
  • Core
  • Feature Setup
  • Reference Library
  • Prerequisites
  • Contributing
  • License

getsentry/sentry-feature-setup

Catalog entry: Skills by Sentry team for their dev team.
Source documentation: https://github.com/getsentry/sentry-for-ai/blob/main/README.md

Function: Configure advanced Sentry features: AI monitoring, OTel pipelines, and alerts

When to use it: Turning on AI monitoring for an existing Sentry project Wiring an existing OTel collector into Sentry Adding alert rules and notifications to a configured project Layering advanced features onto an already-instrumented SDK Standardizing feature rollouts across multiple Sentry projects

Usage guidance is taken from the skill’s own trigger description or usage section.

Source skill menu:

  • Sentry for AI
  • What You Can Do
  • Distribution
  • Build it yourself
  • Skills
  • Core
  • Feature Setup
  • Reference Library
  • Prerequisites
  • Contributing
  • License

getsentry/sentry-setup-ai-monitoring

Catalog entry: Skills by Sentry team for their dev team.
Source documentation: https://github.com/getsentry/sentry-for-ai/blob/main/README.md

Function: Instrument OpenAI, Anthropic, Vercel AI, LangChain, Google GenAI, and Pydantic AI

When to use it: Instrumenting an OpenAI or Anthropic client with Sentry Monitoring LangChain agents in production Wiring Vercel AI SDK calls into Sentry traces Tracking Pydantic AI agent runs for errors and latency Standardizing LLM monitoring across mixed-provider apps

Usage guidance is taken from the skill’s own trigger description or usage section.

Source skill menu:

  • Sentry for AI
  • What You Can Do
  • Distribution
  • Build it yourself
  • Skills
  • Core
  • Feature Setup
  • Reference Library
  • Prerequisites
  • Contributing
  • License

google/cloud/agent-platform-skill-registry

Catalog entry: Skills by Google Cloud
Source documentation: https://github.com/google/skills/blob/main/skills/cloud/agent-platform-skill-registry/SKILL.md

Function: Interact with the Gemini Enterprise Agent Platform Skill Registry to create and search for available skills.

When to use it: Use when a task needs the capability described in this catalog entry: Interact with the Gemini Enterprise Agent Platform Skill Registry to create and search for available skills.

The catalog does not state a separate trigger condition. This usage note is inferred from the published function description.

Source skill menu:

  • Skill Registry
  • Attribution
  • Core Capabilities
  • Core Directives
  • Prerequisites & Authentication
  • Library & Authentication
  • Environment Variables
  • Quickstart
  • Operations

google/cloud/alloydb-basics

Catalog entry: Skills by Google Cloud
Source documentation: https://github.com/google/skills/blob/main/skills/cloud/alloydb-basics/SKILL.md

Function: Manages clusters, instances, and backups for AlloyDB for PostgreSQL, and integrates with AlloyDB model context protocol (MCP) tools for automated database operations.

When to use it: Use when creating, configuring, or administering AlloyDB databases. Do NOT use for general PostgreSQL instances (e.g. Cloud SQL) or other GCP databases.

Usage guidance is taken from the skill’s own trigger description or usage section.

Source skill menu:

  • AlloyDB Basics
  • Attribution
  • Quick Start
  • Reference Directory
  • Directives for Agents
  • Supporting Links

google/cloud/bigquery-basics

Catalog entry: Skills by Google Cloud
Source documentation: https://github.com/google/skills/blob/main/skills/cloud/bigquery-basics/SKILL.md

Function: Manages datasets, tables, and jobs in BigQuery, and integrates with BigQuery ML and Gemini for advanced data analytics and AI-driven insights.

When to use it: Use when you need to interact with BigQuery, run SQL queries, manage BigQuery resources (datasets, tables, views), or perform basic data ingestion and analysis.

Usage guidance is taken from the skill’s own trigger description or usage section.

Source skill menu:

  • BigQuery Basics
  • Attribution
  • Setup and Basic Usage
  • Reference Directory
  • Related Skills

google/cloud/cloud-run-basics

Catalog entry: Skills by Google Cloud
Source documentation: https://github.com/google/skills/blob/main/skills/cloud/cloud-run-basics/SKILL.md

Function: Manages Cloud Run services, jobs, and worker pools.

When to use it: Use when you need to deploy applications responding to HTTP requests (services), run event-triggered or scheduled tasks (jobs), or handle always-on pull-based background processing (worker pools).

Usage guidance is taken from the skill’s own trigger description or usage section.

Source skill menu:

  • Cloud Run Basics
  • Attribution
  • Prerequisites
  • Required roles
  • Deploy a Cloud Run service
  • Deploy a container image to Cloud Run
  • Supported container images
  • Deploy from source code
  • Create and execute a Cloud Run job
  • Deploy a worker pool
  • Deploy a container image
  • Deploy a worker pool from source
  • What to do if a deployment fails:
  • Reference Directory

google/cloud/cloud-sql-basics

Catalog entry: Skills by Google Cloud
Source documentation: https://github.com/google/skills/blob/main/skills/cloud/cloud-sql-basics/SKILL.md

Function: This file generates or explains Cloud SQL resources.

When to use it: Use when a task needs the capability described in this catalog entry: This file generates or explains Cloud SQL resources.

The catalog does not state a separate trigger condition. This usage note is inferred from the published function description.

Source skill menu:

  • Cloud SQL Basics
  • Attribution
  • Prerequisites
  • Quick Start (PostgreSQL)
  • Reference Directory

google/cloud/firebase-basics

Catalog entry: Skills by Google Cloud
Source documentation: https://github.com/google/skills/blob/main/skills/cloud/firebase-basics/SKILL.md

Function: Use this skill whenever you are working on a project that uses Firebase products or services, especially for mobile or web apps.

When to use it: Use when a task needs the capability described in this catalog entry: Use this skill whenever you are working on a project that uses Firebase products or services, especially for mobile or web apps.

The catalog does not state a separate trigger condition. This usage note is inferred from the published function description.

Source skill menu:

  • Firebase Basics
  • Usage Attribution
  • Prerequisites
  • Firebase Usage Principles
  • References
  • Common Issues

google/cloud/gemini-agents-api

Catalog entry: Skills by Google Cloud
Source documentation: https://github.com/google/skills/blob/main/skills/cloud/gemini-agents-api/SKILL.md

Function: Manages custom Agent resources on Gemini Enterprise Agent Platform.

When to use it: Use when the user wants to programmatically create, configure, list, update, or delete stateful, server-managed Agent resources (including mounting files, skills, and tools) before executing conversations.

Usage guidance is taken from the skill’s own trigger description or usage section.

Source skill menu:

  • Gemini Enterprise Agent Platform - Managed Agents API Skill
  • Attribution
  • 1. Authentication & Setup
  • 1. Setup Environment Variables
  • 2. Endpoint URL
  • 2. Programmatic Agent Management (Control Plane CRUD)
  • 1. Create Agent (Long-Running Operation)
  • 2. Polling the LRO Status
  • 3. Get Agent
  • 4. List Agents
  • 5. Update Agent (Patching Configuration)
  • 6. Delete Agent
  • 3. Interacting with Custom Agents (Data Plane)

google/cloud/gemini-api

Catalog entry: Skills by Google Cloud
Source documentation: https://github.com/google/skills/blob/main/skills/cloud/gemini-api/SKILL.md

Function: Guides the usage of the Gemini API on Agent Platform with the Google Gen AI SDK.

When to use it: Use when the user asks about using Gemini in an enterprise environment or explicitly mentions Vertex AI, Google Cloud, or Agent Platform. Guides the usage of the Gemini API on Agent Platform with the Google Gen AI SDK. Covers SDK usage (Python, JS/TS, Go, Java, C#), capabilities like multimodal inputs, tools, media generation, caching, batch prediction, and Live API.

Usage guidance is taken from the skill’s own trigger description or usage section.

Source skill menu:

  • Gemini API in Agent Platform
  • Attribution
  • Core Directives
  • SDKs
  • Authentication & Configuration
  • Application Default Credentials (ADC)
  • Agent Platform in Express Mode
  • Initialization
  • Models
  • Quick Start
  • Python
  • TypeScript/JavaScript
  • Go
  • Java
  • C#/.NET
  • API spec & Documentation (source of truth)

google/cloud/gemini-interactions-api

Catalog entry: Skills by Google Cloud
Source documentation: https://github.com/google/skills/blob/main/skills/cloud/gemini-interactions-api/SKILL.md

Function: Guides the usage of Gemini Interactions API on Gemini Enterprise Agent Platform.

When to use it: Use when the user wants to use the stateful, server-managed Interactions API for multi-turn conversations, background execution, streaming, structured output, and function calling on the Agent Platform.

Usage guidance is taken from the skill’s own trigger description or usage section.

Source skill menu:

  • Gemini Interactions API Skill
  • Attribution
  • 1. Authentication
  • 2. Client Initialization
  • Option A: Environment Variables (Recommended)
  • Option B: Explicit Inline Parameters
  • Option C: Express Mode (API Key)
  • 3. Core Interactions API Usage
  • Quick Start (Single-Turn)
  • Stateful Conversation (Multi-Turn)
  • Real-Time Streaming
  • Structured Output (Pydantic / Polymorphic `response_format`)
  • Function Calling (Agent Tool Use)
  • Agents & Long-Running Tasks
  • 4. Accessing the Interactions API via REST
  • 5. Data Model & Step Types Reference

google/cloud/gke-basics

Catalog entry: Skills by Google Cloud
Source documentation: https://github.com/google/skills/blob/main/skills/cloud/gke-basics/SKILL.md

Function: Plan, create, and configure production-ready Google Kubernetes Engine (GKE) clusters using the golden path Autopilot configuration.

When to use it: Use when creating GKE clusters, fetching kubectl credentials, or deciding between Autopilot and Standard modes. Don’t use for Workload Identity (use gke-workload-identity), GKE networking (use gke-networking), security hardening (use gke-platform-security or gke-workload-security), or cluster upgrades (use gke-upgrades).

Usage guidance is taken from the skill’s own trigger description or usage section.

Source skill menu:

  • GKE Basics & Critical Gotchas
  • Attribution
  • Key Selection Rules: Autopilot vs. Standard
  • Critical Gotchas & Best Practices
  • Reference Directory

google/cloud/google-cloud-networking-observability

Catalog entry: Skills by Google Cloud
Source documentation: https://github.com/google/skills/blob/main/skills/cloud/google-cloud-networking-observability/SKILL.md

Function: Investigates Google Cloud networking issues by analyzing logs, metrics, and diagnostics.

When to use it: Use when investigating dropped network traffic, packet drops, drop reasons, VPC Flow Logs (including Private Service Connect / PSC, serverless / App Engine Direct VPC, and cost estimation), NAT, firewall, or threat logs, querying latency and throughput metrics, or running Connectivity Tests for path diagnostics. Don’t use for generic VM management or non-observability tasks.

Usage guidance is taken from the skill’s own trigger description or usage section.

Source skill menu:

  • Google Cloud Networking Observability Expert
  • Attribution
  • 🛑 Core Directive: Results First
  • Log & Telemetry Overview
  • Procedures
  • 0. Log Source Preference
  • 1. Tool Selection & Discovery
  • 2. Schema Verification & Error Recovery
  • 3. Analysis Guides (Read Only When Needed)
  • Boundaries (CRITICAL)

google/cloud/google-cloud-recipe-onboarding

Catalog entry: Skills by Google Cloud
Source documentation: https://github.com/google/skills/blob/main/skills/cloud/google-cloud-recipe-onboarding/SKILL.md

Function: Guidance for a developer’s first steps on Google Cloud, covering account creation, billing setup, project management, and deploying a first resource.

When to use it: Use when a new developer wants to initialize their first Google Cloud project, configure billing, and verify deployment. Don’t use for enterprise organization setup (use Google Cloud Setup guided flow for that instead). Don’t use for complex multi-project architectures.

Usage guidance is taken from the skill’s own trigger description or usage section.

Source skill menu:

  • Onboarding to Google Cloud
  • Attribution
  • Overview
  • Prerequisites
  • Steps
  • Section 1: Verify Host Tooling Setup
  • Section 2: Authenticate and Route Session
  • Section 3: Select or Instantiate Your Google Cloud Project
  • Section 4: Verify and Link Billing
  • Section 5: Skill Chaining (Spend Controls & Workloads)
  • Validation Logic
  • Additional Resources

google/cloud/google-cloud-waf-cost-optimization

Catalog entry: Skills by Google Cloud
Source documentation: https://github.com/google/skills/blob/main/skills/cloud/google-cloud-waf-cost-optimization/SKILL.md

Function: Generates cost optimization guidance for Google Cloud workloads based on the Google Cloud Well-Architected Framework (WAF).

When to use it: Use when the user asks to analyze Google Cloud spend, reduce cloud bills, rightsize resources (for example, Compute, GKE, Storage, Databases), evaluate discount options (for example, CUDs, SUDs, Spot VMs), or eliminate idle capacity. Do not use for standalone product pricing lookups or non-cost architecture design.

Usage guidance is taken from the skill’s own trigger description or usage section.

Source skill menu:

  • Google Cloud Well-Architected Framework skill for the Cost Optimization pillar
  • Attribution
  • Overview
  • Operational instructions
  • Core principles
  • Relevant Google Cloud products
  • Workload assessment questions
  • Validation checklist

google/cloud/google-cloud-waf-operational-excellence

Catalog entry: Skills by Google Cloud
Source documentation: https://github.com/google/skills/blob/main/skills/cloud/google-cloud-waf-operational-excellence/SKILL.md

Function: Generates operations-focused guidance for Google Cloud workloads based on the design principles and recommendations in the Operational Excellence pillar of the Google Cloud Well-Ar...

When to use it: Use when the user asks about operations-related topics like capacity management, change management, incident and problem management, configuration management, deployment automation using infrastructure as code (IaC), or operational health checks for Google Cloud workloads.

Usage guidance is taken from the skill’s own trigger description or usage section.

Source skill menu:

  • Google Cloud Well-Architected Framework skill for the Operational Excellence pillar
  • Attribution
  • Overview
  • Core principles
  • Relevant Google Cloud products
  • Workload assessment questions
  • Validation checklist

google/cloud/google-cloud-waf-performance-optimization

Catalog entry: Skills by Google Cloud
Source documentation: https://github.com/google/skills/blob/main/skills/cloud/google-cloud-waf-performance-optimization/SKILL.md

Function: Generates performance-focused guidance for Google Cloud workloads based on the design principles and recommendations in the Performance Optimization pillar of the Google Cloud Well...

When to use it: Use when a task needs the capability described in this catalog entry: Generates performance-focused guidance for Google Cloud workloads based on the design principles and recommendations in the Performance Optimization pillar of the Google Cloud Well...

The catalog does not state a separate trigger condition. This usage note is inferred from the published function description.

Source skill menu:

  • Google Cloud Well-Architected Framework skill for the Performance Optimization pillar
  • Attribution
  • Overview
  • Core principles
  • Relevant Google Cloud products
  • Workload assessment questions
  • Validation checklist

google/cloud/google-cloud-waf-reliability

Catalog entry: Skills by Google Cloud
Source documentation: https://github.com/google/skills/blob/main/skills/cloud/google-cloud-waf-reliability/SKILL.md

Function: Generates reliability-focused guidance for Google Cloud workloads based on the design principles and recommendations in the Google Cloud Well-Architected Framework.

When to use it: Use when the user asks about reliability-related topics like workload uptime, designing for high availability (HA) or DR, setting and meeting RTO/RPO targets, SRE best practices, backup strategies, multi-region failover, or fault-tolerant architecture on Google Cloud. Don’t use for other Well-Architected Framework pillars such as Cost Optimization, Operational Excellence, or Security, or for hands-on resource deployment and live incident troubleshooting.

Usage guidance is taken from the skill’s own trigger description or usage section.

Source skill menu:

  • Google Cloud Well-Architected Framework skill for the Reliability pillar
  • Attribution
  • Overview
  • Core principles
  • Relevant Google Cloud products
  • Workload assessment questions
  • Validation checklist

google/cloud/google-cloud-waf-sustainability

Catalog entry: Skills by Google Cloud
Source documentation: https://github.com/google/skills/blob/main/skills/cloud/google-cloud-waf-sustainability/SKILL.md

Function: Generates sustainability-focused guidance for Google Cloud workloads based on the design principles and recommendations in the Google Cloud Well-Architected Framework (WAF).

When to use it: Use when the user asks to assess, design, or optimize Google Cloud workloads for sustainability—including the shared responsibility model, selecting low-carbon regions (CFE%), reducing resource and AI/ML energy waste, designing efficient software and storage lifecycles, or measuring and tracking emissions using Google Cloud Carbon Footprint. Don’t use for financial cost reduction (use google-cloud-waf-cost-optimization), latency and throughput tuning (use google-cloud-waf-performance-optimization), or high availability and disaster recovery (use google-cloud-waf-reliability).

Usage guidance is taken from the skill’s own trigger description or usage section.

Source skill menu:

  • Google Cloud Well-Architected Framework skill for the Sustainability pillar
  • Attribution
  • Overview
  • Core principles
  • Relevant Google Cloud products
  • Workload assessment questions
  • Validation checklist

hashicorp/azure-verified-modules

Catalog entry: Skills by HashiCorp Team for Terraform
Source documentation: https://github.com/hashicorp/agent-skills/blob/main/README.md

Function: Azure Verified Modules (AVM) certification standards for Terraform modules

When to use it: Checking whether a new Terraform module meets AVM certification before submitting it Setting provider version constraints for azurerm and azapi correctly Structuring variables with proper types, descriptions, and nullable settings Writing output blocks that avoid leaking sensitive data or entire resource objects Adding feature toggle variables when introducing new resources in minor versions

Usage guidance is taken from the skill’s own trigger description or usage section.

Source skill menu:

  • HashiCorp Agent Skills
  • Table of Contents
  • Recent Updates
  • Migration from Legacy Plugin IDs and Paths
  • Install an Individual Skill
  • Install a Product Plugin Bundle
  • Claude Code
  • Codex
  • Repository Structure
  • Governance and Support
  • License

hashicorp/new-terraform-provider

Catalog entry: Skills by HashiCorp Team for Terraform
Source documentation: https://github.com/hashicorp/agent-skills/blob/main/README.md

Function: Scaffold a new Terraform provider project using the Plugin Framework

When to use it: Starting a new Terraform provider from a clean directory structure Wiring up the Plugin Framework entry point without reading through boilerplate docs Generating a provider workspace that builds and passes tests out of the box Adding a second provider to a repo without mixing it into an existing workspace Getting a go.mod and dependency tree in place before writing the first resource

Usage guidance is taken from the skill’s own trigger description or usage section.

Source skill menu:

  • HashiCorp Agent Skills
  • Table of Contents
  • Recent Updates
  • Migration from Legacy Plugin IDs and Paths
  • Install an Individual Skill
  • Install a Product Plugin Bundle
  • Claude Code
  • Codex
  • Repository Structure
  • Governance and Support
  • License

hashicorp/provider-actions

Catalog entry: Skills by HashiCorp Team for Terraform
Source documentation: https://github.com/hashicorp/agent-skills/blob/main/README.md

Function: Implement Terraform Provider Actions using the Plugin Framework

When to use it: Adding a post-create action to trigger a downstream service after a resource is provisioned Validating resource state before an update runs by wiring a before_update action Polling an async API until completion inside an action’s Invoke method Writing acceptance tests for actions that require Terraform 1.14.0 or later Documenting a new action with required front matter, examples, and changelog entries

Usage guidance is taken from the skill’s own trigger description or usage section.

Source skill menu:

  • HashiCorp Agent Skills
  • Table of Contents
  • Recent Updates
  • Migration from Legacy Plugin IDs and Paths
  • Install an Individual Skill
  • Install a Product Plugin Bundle
  • Claude Code
  • Codex
  • Repository Structure
  • Governance and Support
  • License

hashicorp/provider-resources

Catalog entry: Skills by HashiCorp Team for Terraform
Source documentation: https://github.com/hashicorp/agent-skills/blob/main/README.md

Function: Implement Terraform Provider resources and data sources using the Plugin Framework

When to use it: Writing Create/Read/Update/Delete handlers for a new Terraform resource Designing schema attributes with validators and plan modifiers Adding import support to an existing resource Writing acceptance tests including disappears tests for drift detection Implementing finder functions with proper not-found error handling

Usage guidance is taken from the skill’s own trigger description or usage section.

Source skill menu:

  • HashiCorp Agent Skills
  • Table of Contents
  • Recent Updates
  • Migration from Legacy Plugin IDs and Paths
  • Install an Individual Skill
  • Install a Product Plugin Bundle
  • Claude Code
  • Codex
  • Repository Structure
  • Governance and Support
  • License

hashicorp/provider-test-patterns

Catalog entry: Skills by HashiCorp Team for Terraform
Source documentation: https://github.com/hashicorp/agent-skills/blob/main/README.md

Function: Acceptance test patterns for Terraform providers using terraform-plugin-testing

When to use it: Writing acceptance tests for a new Terraform provider resource from scratch Debugging a flaky import test with ImportStateVerify failures Adding a regression test that reproduces a specific GitHub issue before fixing it Replacing legacy TestCheckFunc assertions with ConfigStateChecks in existing tests Testing ephemeral resources that must not appear in state after apply

Usage guidance is taken from the skill’s own trigger description or usage section.

Source skill menu:

  • HashiCorp Agent Skills
  • Table of Contents
  • Recent Updates
  • Migration from Legacy Plugin IDs and Paths
  • Install an Individual Skill
  • Install a Product Plugin Bundle
  • Claude Code
  • Codex
  • Repository Structure
  • Governance and Support
  • License

hashicorp/refactor-module

Catalog entry: Skills by HashiCorp Team for Terraform
Source documentation: https://github.com/hashicorp/agent-skills/blob/main/README.md

Function: Transform monolithic Terraform configurations into reusable modules

When to use it: Splitting a 500-line main.tf into separate VPC, compute, and data modules Migrating state references after extracting resources into a module Adding typed variable validation to a module that previously used untyped strings Generating moved blocks to relocate state without destroying and recreating resources Structuring module outputs so downstream modules can reference VPC IDs and subnet maps

Usage guidance is taken from the skill’s own trigger description or usage section.

Source skill menu:

  • HashiCorp Agent Skills
  • Table of Contents
  • Recent Updates
  • Migration from Legacy Plugin IDs and Paths
  • Install an Individual Skill
  • Install a Product Plugin Bundle
  • Claude Code
  • Codex
  • Repository Structure
  • Governance and Support
  • License

hashicorp/run-acceptance-tests

Catalog entry: Skills by HashiCorp Team for Terraform
Source documentation: https://github.com/hashicorp/agent-skills/blob/main/README.md

Function: Run acceptance tests for Terraform providers using Go’s test runner

When to use it: Running a single Terraform provider acceptance test by name Debugging a failing `TestAcc` test with verbose output and debug logging Persisting the Terraform workspace after a test run to inspect leftover state Confirming a passing test is not a false negative by intentionally breaking an assertion Setting up missing provider-specific environment variables when a test reports them absent

Usage guidance is taken from the skill’s own trigger description or usage section.

Source skill menu:

  • HashiCorp Agent Skills
  • Table of Contents
  • Recent Updates
  • Migration from Legacy Plugin IDs and Paths
  • Install an Individual Skill
  • Install a Product Plugin Bundle
  • Claude Code
  • Codex
  • Repository Structure
  • Governance and Support
  • License

hashicorp/terraform-search-import

Catalog entry: Skills by HashiCorp Team for Terraform
Source documentation: https://github.com/hashicorp/agent-skills/blob/main/README.md

Function: Discover existing cloud resources and bulk import them into Terraform state

When to use it: Importing dozens of EC2 instances into Terraform state without writing each import block by hand Auditing which S3 buckets or RDS instances exist in an AWS account but are not yet tracked by any Terraform config Migrating manually provisioned infrastructure to IaC after a team switches to Terraform Filtering resources by tag across multiple AWS regions and generating config for all of them in one pass Scoping down what a specific team owns by querying resources filtered by an Owner tag

Usage guidance is taken from the skill’s own trigger description or usage section.

Source skill menu:

  • HashiCorp Agent Skills
  • Table of Contents
  • Recent Updates
  • Migration from Legacy Plugin IDs and Paths
  • Install an Individual Skill
  • Install a Product Plugin Bundle
  • Claude Code
  • Codex
  • Repository Structure
  • Governance and Support
  • License

hashicorp/terraform-stacks

Catalog entry: Skills by HashiCorp Team for Terraform
Source documentation: https://github.com/hashicorp/agent-skills/blob/main/README.md

Function: Manage infrastructure across multiple environments, regions, and cloud accounts

When to use it: Deploying the same infrastructure to dev, staging, and prod from one component definition Spinning up identical environments across us-east-1, eu-west-1, and ap-southeast-1 using provider for_each Linking a networking stack’s VPC outputs directly into an application stack’s inputs Configuring OIDC workload identity so deployments never store long-lived AWS credentials in state Grouping canary deployments with auto-approve rules that block on any resource deletions

Usage guidance is taken from the skill’s own trigger description or usage section.

Source skill menu:

  • HashiCorp Agent Skills
  • Table of Contents
  • Recent Updates
  • Migration from Legacy Plugin IDs and Paths
  • Install an Individual Skill
  • Install a Product Plugin Bundle
  • Claude Code
  • Codex
  • Repository Structure
  • Governance and Support
  • License

hashicorp/terraform-style-guide

Catalog entry: Skills by HashiCorp Team for Terraform
Source documentation: https://github.com/hashicorp/agent-skills/blob/main/README.md

Function: Generate Terraform HCL code following HashiCorp’s official style conventions

When to use it: Writing new Terraform modules with correct file structure from scratch Reviewing existing HCL configs for naming convention violations Setting up S3 buckets with encryption and public access blocks by default Converting count-based resources to for_each with named instances Adding type, description, and validation blocks to bare variable declarations

Usage guidance is taken from the skill’s own trigger description or usage section.

Source skill menu:

  • HashiCorp Agent Skills
  • Table of Contents
  • Recent Updates
  • Migration from Legacy Plugin IDs and Paths
  • Install an Individual Skill
  • Install a Product Plugin Bundle
  • Claude Code
  • Codex
  • Repository Structure
  • Governance and Support
  • License

hashicorp/terraform-test

Catalog entry: Skills by HashiCorp Team for Terraform
Source documentation: https://github.com/hashicorp/agent-skills/blob/main/README.md

Function: Built-in testing framework for Terraform configurations with .tftest.hcl files

When to use it: Writing .tftest.hcl files to validate module outputs before merging changes Running plan-mode unit tests locally without provisioning real cloud resources Mocking AWS or Azure providers to test conditional logic without credentials Catching variable validation regressions using expect_failures in CI pipelines Testing for_each resource counts and tag propagation across multiple run blocks

Usage guidance is taken from the skill’s own trigger description or usage section.

Source skill menu:

  • HashiCorp Agent Skills
  • Table of Contents
  • Recent Updates
  • Migration from Legacy Plugin IDs and Paths
  • Install an Individual Skill
  • Install a Product Plugin Bundle
  • Claude Code
  • Codex
  • Repository Structure
  • Governance and Support
  • License

hedralab/eskill

Catalog entry: Development and Testing
Source documentation: https://github.com/hedralab/eskill/blob/main/SKILL.md

Function: Meta-skill to build top-tier Agent Skills: spec-compliant SKILL.md, eval loop, validator, market research, numbered-file pipeline

When to use it: Use when a task needs the capability described in this catalog entry: Meta-skill to build top-tier Agent Skills: spec-compliant SKILL.md, eval loop, validator, market research, numbered-file pipeline

The catalog does not state a separate trigger condition. This usage note is inferred from the published function description.

Source skill menu:

  • eskill — Quy trình tạo Agent Skill (12 trụ cột)
  • 12 trụ cột — mỗi trụ 1 kim chỉ nam top-1
  • Quickstart (3 câu — user mới bắt đầu từ đây)
  • 6 bước — BƯỚC 0 quan trọng nhất
  • Quy tắc vàng (học từ sai lầm egram — đừng lặp)
  • Giới hạn (trung thực — khi nào KHÔNG dùng)
  • References

huggingface/hugging-face-jobs

Catalog entry: Skills by Hugging Face Team
Source documentation: https://github.com/huggingface/skills/blob/main/README.md

Function: Run compute jobs and Python scripts on HF infrastructure

When to use it: Running batch inference on thousands of samples using an A10G GPU without provisioning servers Scheduling a daily data processing job that pushes results to a Hub dataset repo Running a vLLM generation pipeline against a Hub dataset and saving outputs back to Hub Testing ML experiment code on cloud GPUs before committing to a full training run Generating synthetic datasets using LLMs on managed TPU or GPU hardware

Usage guidance is taken from the skill’s own trigger description or usage section.

Source skill menu:

  • Hugging Face Skills
  • How do Skills work?
  • Installation
  • Claude Code
  • Codex
  • Gemini CLI
  • Cursor
  • Skills
  • Available skills
  • Using skills in your coding agent
  • Contribute or customize a skill
  • Marketplace
  • Additional references

huggingface/hugging-face-vision-trainer

Catalog entry: Skills by Hugging Face Team
Source documentation: https://github.com/huggingface/skills/blob/main/README.md

Function: Train vision models on HF infrastructure

When to use it: Training a custom object detector on COCO-format data using D-FINE or RT-DETR v2 on cloud GPUs Fine-tuning a MobileNetV3 or ViT classifier on a Hub image dataset without a local GPU Fine-tuning SAM2 for image matting or segmentation using bounding box or point prompts Running the dataset inspector to catch column format mismatches before submitting a GPU training job Saving fine-tuned detection or classification checkpoints directly to the Hugging Face Hub from ephemeral cloud jobs

Usage guidance is taken from the skill’s own trigger description or usage section.

Source skill menu:

  • Hugging Face Skills
  • How do Skills work?
  • Installation
  • Claude Code
  • Codex
  • Gemini CLI
  • Cursor
  • Skills
  • Available skills
  • Using skills in your coding agent
  • Contribute or customize a skill
  • Marketplace
  • Additional references

huggingface/huggingface-gradio

Catalog entry: Skills by Hugging Face Team
Source documentation: https://github.com/huggingface/skills/blob/main/skills/huggingface-gradio/SKILL.md

Function: Build Gradio apps and deploy to HF Spaces

When to use it: Use when creating or editing Gradio apps, components, event listeners, layouts, or chatbots.

Usage guidance is taken from the skill’s own trigger description or usage section.

Source skill menu:

  • Gradio
  • Guides
  • Core Patterns
  • Key Component Signatures
  • `Textbox(value: str | I18nData | Callable | None = None, type: Literal[‘text’, ‘password’, ‘email’] = “text”, lines: int = 1, max_lines: int | None = None, placeholder: str | I18nData | None = None, label: str | I18nData | None = None, info: str | I18nData | None = None, every: Timer | float | None = None, inputs: Component | Sequence[Component] | set[Component] | None = None, show_label: bool | None = None, container: bool = True, scale: int | None = None, min_width: int = 160, interactive: bool | None = None, visible: bool | Literal[‘hidden’] = True, elem_id: str | None = None, autofocus: bool = False, autoscroll: bool = True, elem_classes: list[str] | str | None = None, render: bool = True, key: int | str | tuple[int | str, ...] | None = None, preserved_by_key: list[str] | str | None = “value”, text_align: Literal[‘left’, ‘right’] | None = None, rtl: bool = False, buttons: list[Literal[‘copy’] | Button] | None = None, max_length: int | None = None, submit_btn: str | bool | None = False, stop_btn: str | bool | None = False, html_attributes: InputHTMLAttributes | None = None)`
  • `Number(value: float | Callable | None = None, label: str | I18nData | None = None, placeholder: str | I18nData | None = None, info: str | I18nData | None = None, every: Timer | float | None = None, inputs: Component | Sequence[Component] | set[Component] | None = None, show_label: bool | None = None, container: bool = True, scale: int | None = None, min_width: int = 160, interactive: bool | None = None, visible: bool | Literal[‘hidden’] = True, elem_id: str | None = None, elem_classes: list[str] | str | None = None, render: bool = True, key: int | str | tuple[int | str, ...] | None = None, preserved_by_key: list[str] | str | None = “value”, buttons: list[Button] | None = None, precision: int | None = None, minimum: float | None = None, maximum: float | None = None, step: float = 1)`
  • `Slider(minimum: float = 0, maximum: float = 100, value: float | Callable | None = None, step: float | None = None, precision: int | None = None, label: str | I18nData | None = None, info: str | I18nData | None = None, every: Timer | float | None = None, inputs: Component | Sequence[Component] | set[Component] | None = None, show_label: bool | None = None, container: bool = True, scale: int | None = None, min_width: int = 160, interactive: bool | None = None, visible: bool | Literal[‘hidden’] = True, elem_id: str | None = None, elem_classes: list[str] | str | None = None, render: bool = True, key: int | str | tuple[int | str, ...] | None = None, preserved_by_key: list[str] | str | None = “value”, randomize: bool = False, buttons: list[Literal[‘reset’]] | None = None)`
  • `Checkbox(value: bool | Callable = False, label: str | I18nData | None = None, info: str | I18nData | None = None, every: Timer | float | None = None, inputs: Component | Sequence[Component] | set[Component] | None = None, show_label: bool | None = None, container: bool = True, scale: int | None = None, min_width: int = 160, interactive: bool | None = None, visible: bool | Literal[‘hidden’] = True, elem_id: str | None = None, elem_classes: list[str] | str | None = None, render: bool = True, key: int | str | tuple[int | str, ...] | None = None, preserved_by_key: list[str] | str | None = “value”, buttons: list[Button] | None = None)`
  • `Dropdown(choices: Sequence[str | int | float | tuple[str, str | int | float]] | None = None, value: str | int | float | Sequence[str | int | float] | Callable | DefaultValue | None = DefaultValue(), type: Literal[‘value’, ‘index’] = “value”, multiselect: bool | None = None, allow_custom_value: bool = False, max_choices: int | None = None, filterable: bool = True, label: str | I18nData | None = None, info: str | I18nData | None = None, every: Timer | float | None = None, inputs: Component | Sequence[Component] | set[Component] | None = None, show_label: bool | None = None, container: bool = True, scale: int | None = None, min_width: int = 160, interactive: bool | None = None, visible: bool | Literal[‘hidden’] = True, elem_id: str | None = None, elem_classes: list[str] | str | None = None, render: bool = True, key: int | str | tuple[int | str, ...] | None = None, preserved_by_key: list[str] | str | None = “value”, buttons: list[Button] | None = None)`
  • `Radio(choices: Sequence[str | int | float | tuple[str, str | int | float]] | None = None, value: str | int | float | Callable | None = None, type: Literal[‘value’, ‘index’] = “value”, label: str | I18nData | None = None, info: str | I18nData | None = None, every: Timer | float | None = None, inputs: Component | Sequence[Component] | set[Component] | None = None, show_label: bool | None = None, container: bool = True, scale: int | None = None, min_width: int = 160, interactive: bool | None = None, visible: bool | Literal[‘hidden’] = True, elem_id: str | None = None, elem_classes: list[str] | str | None = None, render: bool = True, key: int | str | tuple[int | str, ...] | None = None, preserved_by_key: list[str] | str | None = “value”, rtl: bool = False, buttons: list[Button] | None = None)`
  • `Image(value: str | PIL.Image.Image | np.ndarray | Callable | None = None, format: str = “webp”, height: int | str | None = None, width: int | str | None = None, image_mode: Literal[‘1’, ‘L’, ‘P’, ‘RGB’, ‘RGBA’, ‘CMYK’, ‘YCbCr’, ‘LAB’, ‘HSV’, ‘I’, ‘F’] | None = “RGB”, sources: list[Literal[‘upload’, ‘webcam’, ‘clipboard’]] | Literal[‘upload’, ‘webcam’, ‘clipboard’] | None = None, type: Literal[‘numpy’, ‘pil’, ‘filepath’] = “numpy”, label: str | I18nData | None = None, every: Timer | float | None = None, inputs: Component | Sequence[Component] | set[Component] | None = None, show_label: bool | None = None, buttons: list[Literal[‘download’, ‘share’, ‘fullscreen’] | Button] | None = None, container: bool = True, scale: int | None = None, min_width: int = 160, interactive: bool | None = None, visible: bool | Literal[‘hidden’] = True, streaming: bool = False, elem_id: str | None = None, elem_classes: list[str] | str | None = None, render: bool = True, key: int | str | tuple[int | str, ...] | None = None, preserved_by_key: list[str] | str | None = “value”, webcam_options: WebcamOptions | None = None, placeholder: str | None = None, watermark: WatermarkOptions | None = None)`
  • `Audio(value: str | Path | tuple[int, np.ndarray] | Callable | None = None, sources: list[Literal[‘upload’, ‘microphone’]] | Literal[‘upload’, ‘microphone’] | None = None, type: Literal[‘numpy’, ‘filepath’] = “numpy”, label: str | I18nData | None = None, every: Timer | float | None = None, inputs: Component | Sequence[Component] | set[Component] | None = None, show_label: bool | None = None, container: bool = True, scale: int | None = None, min_width: int = 160, interactive: bool | None = None, visible: bool | Literal[‘hidden’] = True, streaming: bool = False, elem_id: str | None = None, elem_classes: list[str] | str | None = None, render: bool = True, key: int | str | tuple[int | str, ...] | None = None, preserved_by_key: list[str] | str | None = “value”, format: Literal[‘wav’, ‘mp3’] | None = None, autoplay: bool = False, editable: bool = True, buttons: list[Literal[‘download’, ‘share’] | Button] | None = None, waveform_options: WaveformOptions | dict | None = None, loop: bool = False, recording: bool = False, subtitles: str | Path | list[dict[str, Any]] | None = None, playback_position: float = 0)`
  • `Video(value: str | Path | Callable | None = None, format: str | None = None, sources: list[Literal[‘upload’, ‘webcam’]] | Literal[‘upload’, ‘webcam’] | None = None, height: int | str | None = None, width: int | str | None = None, label: str | I18nData | None = None, every: Timer | float | None = None, inputs: Component | Sequence[Component] | set[Component] | None = None, show_label: bool | None = None, container: bool = True, scale: int | None = None, min_width: int = 160, interactive: bool | None = None, visible: bool | Literal[‘hidden’] = True, elem_id: str | None = None, elem_classes: list[str] | str | None = None, render: bool = True, key: int | str | tuple[int | str, ...] | None = None, preserved_by_key: list[str] | str | None = “value”, webcam_options: WebcamOptions | None = None, include_audio: bool | None = None, autoplay: bool = False, buttons: list[Literal[‘download’, ‘share’] | Button] | None = None, loop: bool = False, streaming: bool = False, watermark: WatermarkOptions | None = None, subtitles: str | Path | list[dict[str, Any]] | None = None, playback_position: float = 0)`
  • `File(value: str | list[str] | Callable | None = None, file_count: Literal[‘single’, ‘multiple’, ‘directory’] = “single”, file_types: list[str] | None = None, type: Literal[‘filepath’, ‘binary’] = “filepath”, label: str | I18nData | None = None, every: Timer | float | None = None, inputs: Component | Sequence[Component] | set[Component] | None = None, show_label: bool | None = None, container: bool = True, scale: int | None = None, min_width: int = 160, height: int | str | float | None = None, interactive: bool | None = None, visible: bool | Literal[‘hidden’] = True, elem_id: str | None = None, elem_classes: list[str] | str | None = None, render: bool = True, key: int | str | tuple[int | str, ...] | None = None, preserved_by_key: list[str] | str | None = “value”, allow_reordering: bool = False, buttons: list[Button] | None = None)`
  • `Chatbot(value: list[MessageDict | Message] | Callable | None = None, label: str | I18nData | None = None, every: Timer | float | None = None, inputs: Component | Sequence[Component] | set[Component] | None = None, show_label: bool | None = None, container: bool = True, scale: int | None = None, min_width: int = 160, visible: bool | Literal[‘hidden’] = True, elem_id: str | None = None, elem_classes: list[str] | str | None = None, autoscroll: bool = True, render: bool = True, key: int | str | tuple[int | str, ...] | None = None, preserved_by_key: list[str] | str | None = “value”, height: int | str | None = 400, resizable: bool = False, max_height: int | str | None = None, min_height: int | str | None = None, editable: Literal[‘user’, ‘all’] | None = None, latex_delimiters: list[dict[str, str | bool]] | None = None, rtl: bool = False, buttons: list[Literal[‘share’, ‘copy’, ‘copy_all’] | Button] | None = None, watermark: str | None = None, avatar_images: tuple[str | Path | None, str | Path | None] | None = None, sanitize_html: bool = True, render_markdown: bool = True, feedback_options: list[str] | tuple[str, ...] | None = (‘Like’, ‘Dislike’), feedback_value: Sequence[str | None] | None = None, line_breaks: bool = True, layout: Literal[‘panel’, ‘bubble’] | None = None, placeholder: str | None = None, examples: list[ExampleMessage] | None = None, allow_file_downloads: = True, group_consecutive_messages: bool = True, allow_tags: list[str] | bool = True, reasoning_tags: list[tuple[str, str]] | None = None, like_user_message: bool = False)`
  • `Button(value: str | I18nData | Callable = “Run”, every: Timer | float | None = None, inputs: Component | Sequence[Component] | set[Component] | None = None, variant: Literal[‘primary’, ‘secondary’, ‘stop’, ‘huggingface’] = “secondary”, size: Literal[‘sm’, ‘md’, ‘lg’] = “lg”, icon: str | Path | None = None, link: str | None = None, link_target: Literal[‘_self’, ‘_blank’, ‘_parent’, ‘_top’] = “_self”, visible: bool | Literal[‘hidden’] = True, interactive: bool = True, elem_id: str | None = None, elem_classes: list[str] | str | None = None, render: bool = True, key: int | str | tuple[int | str, ...] | None = None, preserved_by_key: list[str] | str | None = “value”, scale: int | None = None, min_width: int | None = None)`

hyperb1iss/unifly

Catalog entry: Specialized Domains
Source documentation: https://github.com/hyperb1iss/unifly/blob/main/skills/unifly/SKILL.md

Function: Inspect and manage Ubiquiti UniFi networks through the unifly CLI

When to use it: Use when a task needs the capability described in this catalog entry: Inspect and manage Ubiquiti UniFi networks through the unifly CLI

The catalog does not state a separate trigger condition. This usage note is inferred from the published function description.

Source skill menu:

  • unifly

microsoft/azure-mgmt-weightsandbiases-dotnet

Catalog entry: Skills by Microsoft
Source documentation: https://github.com/microsoft/skills/blob/main/.github/plugins/azure-sdk-dotnet/skills/azure-mgmt-weightsandbiases-dotnet/SKILL.md

Function: Weights & Biases deployment management

When to use it: Provisioning a W&B instance into an existing Azure resource group Configuring Entra ID SSO so teams log in with corporate credentials Tagging W&B instances for cost center tracking across ML teams Listing all W&B deployments across a subscription to audit usage Updating region and subdomain settings on an existing W&B instance

Usage guidance is taken from the skill’s own trigger description or usage section.

Source skill menu:

  • Azure.ResourceManager.WeightsAndBiases (.NET)
  • Installation
  • Environment Variables
  • Authentication
  • Resource Hierarchy
  • Core Workflows
  • 1. Create Weights & Biases Instance
  • 2. Get Existing Instance
  • 3. List All Instances
  • 4. Configure Single Sign-On (SSO)
  • 5. Update Instance
  • 6. Delete Instance
  • 7. Check Resource Name Availability
  • Key Types Reference
  • Available Regions
  • Marketplace Offer Details

microsoft/azure-monitor-ingestion-java

Catalog entry: Skills by Microsoft
Source documentation: https://github.com/microsoft/skills/blob/main/.github/plugins/azure-sdk-java/skills/azure-monitor-ingestion-java/SKILL.md

Function: Custom log ingestion to Azure Monitor

When to use it: Shipping Java application logs to a custom Log Analytics table for centralized querying Batching and uploading audit events from a Spring Boot service to Azure Monitor Routing structured Java logs into CommonSecurityLog or Syslog built-in tables via DCR Handling partial upload failures in bulk log ingestion pipelines without aborting the entire batch Ingesting high-volume telemetry asynchronously using LogsIngestionAsyncClient in reactive Java apps

Usage guidance is taken from the skill’s own trigger description or usage section.

Source skill menu:

  • Azure Monitor Ingestion SDK for Java
  • Installation
  • Prerequisites
  • Environment Variables
  • Client Creation
  • Synchronous Client
  • Asynchronous Client
  • Key Concepts
  • Core Operations
  • Upload Custom Logs
  • Upload with Concurrency
  • Upload with Error Handling
  • Async Upload with Reactor
  • Log Entry Model Example
  • Error Handling
  • Best Practices

microsoft/azure-monitor-ingestion-py

Catalog entry: Skills by Microsoft
Source documentation: https://github.com/microsoft/skills/blob/main/.github/plugins/azure-sdk-python/skills/azure-monitor-ingestion-py/SKILL.md

Function: Custom log ingestion to Azure Monitor

When to use it: Sending application logs from a Python service to Log Analytics for querying Ingesting security audit records into a custom table in Azure Monitor Uploading batch log exports from JSON files into a DCR-defined schema Piping async high-throughput event streams into Log Analytics without manual batching Routing logs to Azure Government or sovereign cloud endpoints

Usage guidance is taken from the skill’s own trigger description or usage section.

Source skill menu:

  • Azure Monitor Ingestion SDK for Python
  • Installation
  • Environment Variables
  • Prerequisites
  • Authentication & Lifecycle
  • Upload Custom Logs
  • Upload from JSON File
  • Custom Error Handling
  • Ignore Errors
  • Async Client
  • Sovereign Clouds
  • Batching Behavior
  • Client Types
  • Key Concepts
  • DCR Stream Name Format
  • Best Practices

microsoft/azure-monitor-opentelemetry-exporter-java

Catalog entry: Skills by Microsoft
Source documentation: https://github.com/microsoft/skills/blob/main/.github/plugins/azure-sdk-java/skills/azure-monitor-opentelemetry-exporter-java/SKILL.md

Function: OpenTelemetry export to Azure Monitor

When to use it: Sending distributed trace data from a Java microservice to Application Insights Adding span attributes like order ID and customer tier to traces for debugging Recording exceptions on spans so they appear in Azure Monitor Tracking HTTP request counts and latency as metrics in Application Insights Migrating from the deprecated exporter to the autoconfigure package

Usage guidance is taken from the skill’s own trigger description or usage section.

Source skill menu:

  • Azure Monitor OpenTelemetry Exporter for Java
  • Installation (Deprecated)
  • Recommended: Use Autoconfigure Instead
  • Environment Variables
  • Basic Setup with Autoconfigure (Recommended)
  • Using Environment Variable
  • With Explicit Connection String
  • Creating Spans
  • Adding Span Attributes
  • Custom Span Processor
  • Nested Spans
  • Recording Exceptions
  • Metrics (via OpenTelemetry)
  • Key Concepts
  • Migration to Autoconfigure
  • Migration Steps

microsoft/azure-monitor-opentelemetry-exporter-py

Catalog entry: Skills by Microsoft
Source documentation: https://github.com/microsoft/skills/blob/main/.github/plugins/azure-sdk-python/skills/azure-monitor-opentelemetry-exporter-py/SKILL.md

Function: OpenTelemetry export to Application Insights

When to use it: Routing OpenTelemetry spans from a custom tracer pipeline into Application Insights Sampling 10% of production traces with ApplicationInsightsSampler across distributed services Sending Python logging output to Application Insights using the log exporter and LoggingHandler Connecting to Azure Government endpoints with sovereign cloud credentials Retrying failed telemetry exports using local offline storage when the ingestion endpoint is unreachable

Usage guidance is taken from the skill’s own trigger description or usage section.

Source skill menu:

  • Azure Monitor OpenTelemetry Exporter for Python
  • Installation
  • Environment Variables
  • Authentication & Lifecycle
  • When to Use
  • Trace Exporter
  • Metric Exporter
  • Log Exporter
  • From Environment Variable
  • Azure AD Authentication
  • Sampling
  • Offline Storage
  • Disable Offline Storage
  • Sovereign Clouds
  • Exporter Types
  • Configuration Options

microsoft/azure-monitor-opentelemetry-py

Catalog entry: Skills by Microsoft
Source documentation: https://github.com/microsoft/skills/blob/main/.github/plugins/azure-sdk-python/skills/azure-monitor-opentelemetry-py/SKILL.md

Function: One-line Application Insights setup

When to use it: Adding Application Insights to a Flask API without touching route handlers Tracing database queries in Django through psycopg2 auto-instrumentation Sampling 10% of requests in a high-traffic FastAPI service Attaching a service name to traces so Application Map shows the right node Switching from key-based auth to Azure AD credentials for a production workload

Usage guidance is taken from the skill’s own trigger description or usage section.

Source skill menu:

  • Azure Monitor OpenTelemetry Distro for Python
  • Installation
  • Environment Variables
  • Authentication & Lifecycle
  • Quick Start
  • Explicit Connection String
  • With Flask
  • With Django
  • With FastAPI
  • Custom Traces
  • Custom Metrics
  • Custom Logs
  • Sampling
  • Cloud Role Name
  • Disable Specific Instrumentations
  • Enable Live Metrics

microsoft/azure-monitor-opentelemetry-ts

Catalog entry: Skills by Microsoft
Source documentation: https://github.com/microsoft/skills/blob/main/.github/plugins/azure-sdk-typescript/skills/azure-monitor-opentelemetry-ts/SKILL.md

Function: Application Insights tracing and metrics

When to use it: Use when adding distributed tracing, metrics, and logs to Node.js applications with Application Insights.

Usage guidance is taken from the skill’s own trigger description or usage section.

Source skill menu:

  • Azure Monitor OpenTelemetry SDK for TypeScript
  • Installation
  • Environment Variables
  • Quick Start (Auto-Instrumentation)
  • ESM Support (Node.js 18.19+)
  • Full Configuration
  • Custom Traces
  • Custom Metrics
  • Manual Exporter Setup
  • Trace Exporter
  • Metric Exporter
  • Log Exporter
  • Custom Logs Ingestion
  • Custom Span Processor
  • Sampling
  • Shutdown

microsoft/azure-monitor-query-java

Catalog entry: Skills by Microsoft
Source documentation: https://github.com/microsoft/skills/blob/main/.github/plugins/azure-sdk-java/skills/azure-monitor-query-java/SKILL.md

Function: Query Azure Monitor logs and metrics

When to use it: Running Kusto queries against a Log Analytics workspace from a Java application Fetching CPU or memory metrics for an Azure VM over a custom time range Batching multiple log queries into a single API call to reduce round trips Mapping Log Analytics query results directly to Java model classes Querying metrics across multiple Azure resources in one request

Usage guidance is taken from the skill’s own trigger description or usage section.

Source skill menu:

  • Azure Monitor Query SDK for Java
  • Installation
  • Prerequisites
  • Environment Variables
  • Client Creation
  • LogsQueryClient (Sync)
  • LogsQueryAsyncClient
  • MetricsQueryClient (Sync)
  • MetricsQueryAsyncClient
  • Sovereign Cloud Configuration
  • Key Concepts
  • Logs Query Operations
  • Basic Query
  • Query by Resource ID
  • Map Results to Custom Model
  • Batch Query

microsoft/azure-monitor-query-py

Catalog entry: Skills by Microsoft
Source documentation: https://github.com/microsoft/skills/blob/main/.github/plugins/azure-sdk-python/skills/azure-monitor-query-py/SKILL.md

Function: Query Azure Monitor logs and metrics

When to use it: Running Kusto queries against Log Analytics to find slow API requests over a time window Pulling CPU and network metrics from an Azure VM at 5-minute granularity Batch querying AppRequests and AppExceptions in a single round trip Converting Log Analytics query results into a pandas DataFrame for analysis Filtering Azure Blob Storage request metrics by API name dimension

Usage guidance is taken from the skill’s own trigger description or usage section.

Source skill menu:

  • Azure Monitor Query SDK for Python
  • Installation
  • Environment Variables
  • Authentication & Lifecycle
  • Logs Query Client
  • Basic Query
  • Query with Time Range
  • Convert to DataFrame
  • Batch Query
  • Handle Partial Results
  • Metrics Query Client
  • Query Resource Metrics
  • Aggregations
  • Filter by Dimension
  • List Metric Definitions
  • List Metric Namespaces

microsoft/cloud-solution-architect

Catalog entry: Skills by Microsoft
Source documentation: https://github.com/microsoft/skills/blob/main/README.md

Function: Design well-architected Azure cloud systems

When to use it: Selecting between microservices and N-tier for a new Azure workload Mapping WAF pillar tradeoffs during a production architecture review Choosing between Service Bus and Event Hubs for a messaging pipeline Applying the circuit breaker and retry patterns to a failing downstream dependency Writing an Architecture Decision Record for a multi-region Cosmos DB setup

Usage guidance is taken from the skill’s own trigger description or usage section.

Source skill menu:

  • Agent Skills
  • Quick Start
  • What’s Inside
  • Skill Catalog
  • Core
  • Foundry (Language-Agnostic)
  • Python
  • .NET
  • TypeScript
  • Java
  • Rust
  • Repository Structure
  • Plugins
  • MCP Servers
  • Additional Resources
  • Agents

mongodb/mongodb-connection

Catalog entry: Skills by MongoDB
Source documentation: https://github.com/mongodb/agent-skills/blob/main/skills/mongodb-connection/SKILL.md

Function: Optimize MongoDB client connection pools, timeouts, and serverless patterns

When to use it: Use this skill when working/updating/reviewing on functions that instantiate or configure a MongoDB client (eg, when calling `connect()`), configuring connection pools, troubleshooting connection errors (ECONNREFUSED, timeouts, pool exhaustion), optimizing performance issues related to connections. This includes scenarios like building serverless functions with MongoDB, creating API endpoints that use MongoDB, optimizing high-traffic MongoDB applications, creating long-running tasks and concurrency, or debugging connection-related failures.

Usage guidance is taken from the skill’s own trigger description or usage section.

Source skill menu:

  • MongoDB Connection Optimizer
  • Core Principle: Context Before Configuration
  • Understanding How Connection Pools Work
  • Configuration Design
  • Calculating Initial Pool Size
  • Configuration Scenarios
  • Troubleshooting Connection Issues
  • Guidelines
  • Pool Exhaustion
  • Connection Timeouts (ECONNREFUSED, SocketTimeout)
  • Connection Churn
  • High Latency
  • Environmental Context (MANDATORY)
  • Parameters that inform a pool configuration
  • Advising on Monitoring & Iteration
  • When creating code

mongodb/mongodb-natural-language-querying

Catalog entry: Skills by MongoDB
Source documentation: https://github.com/mongodb/agent-skills/blob/main/skills/mongodb-natural-language-querying/SKILL.md

Function: Translate natural language into MongoDB queries and aggregation pipelines

When to use it: Use this skill whenever the user asks to write, create, or generate MongoDB queries, wants to filter/query/aggregate data in MongoDB, asks “how do I query...“, needs help with query syntax, or discusses finding/filtering/grouping MongoDB documents. Also use for translating SQL-like requests to MongoDB syntax. Does NOT handle Atlas Search ($search operator), vector/semantic search ($vectorSearch operator), fuzzy matching, autocomplete indexes, or relevance scoring - use search-and-ai for those. Does NOT analyze or optimize existing queries - use mongodb-query-optimizer for that. Does NOT handle aggregation pipelin

Usage guidance is taken from the skill’s own trigger description or usage section.

Source skill menu:

  • MongoDB Natural Language Querying
  • Query Generation Process
  • 1. Gather Context Using MCP Tools
  • 2. Analyze Context and Validate Fields
  • 3. Choose Query Type: Find vs Aggregation
  • 4. Format Your Response
  • Best Practices
  • Query Quality
  • Aggregation Pipeline Quality
  • Error Prevention
  • Schema Analysis
  • Sample Document Usage
  • Error Handling
  • Example Workflow
  • Managing Context Size

neondatabase/neon-postgres

Catalog entry: Skills by Neon
Source documentation: https://github.com/neondatabase/agent-skills/blob/main/skills/neon-postgres/SKILL.md

Function: Best practices for Neon Serverless Postgres

When to use it: Use when the work is an existing DATABASE_URL, SQL, schema, inspect, or search. New backends, Auth, files, Functions, and LLM calls go to the parent `neon` skill. Live queries, reactive UIs, and realtime data go to `neon-realtime`. Also use for “@neondatabase/serverless”, “@neon/neon-js”, “neon inspect db”, “semantic search”, “vector search”, “full-text search”, “BM25”, or “hybrid search”.

Usage guidance is taken from the skill’s own trigger description or usage section.

Source skill menu:

  • Lakebase Postgres
  • Setup Flow
  • 1. Select the organization and project
  • 2. Get the connection string
  • 3. Pick the connection method and driver
  • 4. Set up the schema
  • Branching
  • Migrations
  • Troubleshooting and Neon-Specific Performance
  • Choose CLI or MCP
  • Pick the Diagnostic
  • Interpret Results Safely
  • Inspect Neon Cache Behavior Per Query
  • Performance Workflow
  • Autoscaling
  • Scale to Zero

netlify/netlify-ai-gateway

Catalog entry: Skills by Netlify Team
Source documentation: https://github.com/netlify/context-and-tools/blob/main/skills/netlify-ai-gateway/SKILL.md

Function: Access AI models via unified gateway endpoint

When to use it: Calling GPT-4o or Claude from a Netlify Function without storing API keys in environment variables Switching between OpenAI and Anthropic models by changing a single model string Adding AI chat endpoints to a Netlify site using the existing OpenAI SDK Testing AI features locally with netlify dev using the same gateway that runs in production Monitoring AI model usage and costs through Netlify’s dashboard instead of each provider’s console

Usage guidance is taken from the skill’s own trigger description or usage section.

Source skill menu:

  • Netlify AI Gateway
  • Footguns (read first)
  • Where code goes
  • Provider SDKs (instantiate with no args)
  • Env vars — which to use
  • Full example (Vite + React + Function)
  • Local development
  • Billing, limits, constraints
  • References
  • Netlify house rules (ai-gateway)

netlify/netlify-blobs

Catalog entry: Skills by Netlify Team
Source documentation: https://github.com/netlify/context-and-tools/blob/main/skills/netlify-blobs/SKILL.md

Function: Key-value object storage for files and data

When to use it: Use when persisting user file uploads (images/documents), caching computed output from functions or Background Functions, serving downloadable assets, storing JSON blobs keyed by ID, or seeding deploy-specific data. Reach for this for key/value or object storage from Functions, Edge Functions, or Build Plugins — not for per-user, transactional, or relational data (use Netlify DB for that). Triggers include “save an uploaded file”, “cache API results”, “store generated site map”, “key/value store for a function”, or “file uploads without a database”.

Usage guidance is taken from the skill’s own trigger description or usage section.

Source skill menu:

  • Netlify Blobs
  • Choosing a store type
  • Core writes and reads
  • Persisting a user upload (Function)
  • Reading (Function)
  • Metadata and conditional reads
  • Concurrency: atomic conditional writes
  • Listing
  • Deleting
  • Expiration (no server-side TTL)
  • Consistency
  • Regions
  • File-based uploads (no build plugin)
  • Access control (default to private)
  • Constraints
  • When an operation fails

netlify/netlify-caching

Catalog entry: Skills by Netlify Team
Source documentation: https://github.com/netlify/context-and-tools/blob/main/skills/netlify-caching/SKILL.md

Function: Configure CDN caching and cache purging

When to use it: Use when you add caching or cache-control headers to a function response, tune cache TTL or stale-while-revalidate, set up the durable cache, vary a cache key by query/header/cookie/country/language, purge or invalidate the cache by site or cache tag, use the programmatic Cache API (caches.open/match/put) or @netlify/cache helpers (fetchWithCache/cacheHeaders/getCacheStatus), speed up an expensive API call, add ISR or on-demand revalidation, or debug why a response is or isn’t cached via the Cache-Status header.

Usage guidance is taken from the skill’s own trigger description or usage section.

Source skill menu:

  • Netlify caching
  • Cache-control header to reach for
  • Footguns (read first)
  • Directives
  • Cache key variation — `Netlify-Vary`
  • Cache tags & opt-out
  • On-demand invalidation (purge)
  • Cache API (`caches` global)
  • `@netlify/cache` module
  • `cacheHeaders(settings)` → header object
  • `fetchWithCache(resource, options?, cacheSettings?)`
  • `getCacheStatus(response | headers | headerString)`
  • `needsRevalidation(response)` → boolean
  • Durable cache
  • Debugging with `Cache-Status`
  • Netlify house rules (caching)

netlify/netlify-cli-and-deploy

Catalog entry: Skills by Netlify Team
Source documentation: https://github.com/netlify/context-and-tools/blob/main/README.md

Function: CLI setup, local dev, and deployment workflows

When to use it: Deploying a static site to production without a Git remote Exporting environment variables from Netlify to a local .env file Running local dev with Netlify Functions and redirects injected via netlify dev Setting context-specific environment variables for deploy previews vs production Linking an existing project to a Netlify site by Git remote URL

Usage guidance is taken from the skill’s own trigger description or usage section.

Source skill menu:

  • Netlify Context and Tools
  • Skills
  • References
  • Installation
  • Other ways to install
  • Hosted skills, manifest, and npm
  • Install skills and keep them current
  • Design Principles
  • Contributing
  • Generated outputs — do not edit them directly

netlify/netlify-config

Catalog entry: Skills by Netlify Team
Source documentation: https://github.com/netlify/context-and-tools/blob/main/skills/netlify-config/SKILL.md

Function: Reference for netlify.toml site configuration

When to use it: Use when setting a build command or publish directory, adding redirects or rewrites or proxies, adding an SPA fallback rewrite, setting custom response headers or basic auth, managing environment variables and secrets, scoping vars per deploy context, marking a var as secret, disabling secret scanning, configuring functions bundling, ignoring builds, or wiring up a monorepo or JavaScript SPA on Netlify.

Usage guidance is taken from the skill’s own trigger description or usage section.

Source skill menu:

  • Netlify configuration
  • Modern vs legacy syntax to reach for
  • `netlify.toml` build + contexts
  • Redirects and rewrites
  • Proxies
  • Custom headers
  • Functions
  • Environment variables
  • Injecting env values into headers/redirects
  • Useful read-only build vars
  • Secrets Controller
  • Sensitive variable policy (public repos only)
  • Ignore builds
  • Monorepos
  • JavaScript SPAs
  • Netlify Dev `[dev]`

netlify/netlify-db

Catalog entry: Skills by Netlify Team
Source documentation: https://github.com/netlify/context-and-tools/blob/main/README.md

Function: Managed Postgres with deploy preview branching

When to use it: Running SQL queries against structured app data from Netlify functions Setting up Drizzle ORM schemas and generating typed migrations Testing database migrations on deploy preview branches before merging to production Querying and filtering relational data that grows over time Accessing a Postgres database locally through netlify dev without manual connection setup

Usage guidance is taken from the skill’s own trigger description or usage section.

Source skill menu:

  • Netlify Context and Tools
  • Skills
  • References
  • Installation
  • Other ways to install
  • Hosted skills, manifest, and npm
  • Install skills and keep them current
  • Design Principles
  • Contributing
  • Generated outputs — do not edit them directly

netlify/netlify-deploy

Catalog entry: Skills by Netlify Team
Source documentation: https://github.com/netlify/context-and-tools/blob/main/skills/netlify-deploy/SKILL.md

Function: Automated deployment workflow for Netlify sites

When to use it: Deploying a Vite or Next.js app to a Netlify preview URL before merging a PR Linking a local project folder to an existing Netlify site by Git remote Creating a new Netlify site and configuring build settings from scratch Pushing a production deploy after verifying a preview URL looks correct Troubleshooting a failed deploy by checking build command and publish directory

Usage guidance is taken from the skill’s own trigger description or usage section.

Source skill menu:

  • Netlify deploy
  • Modern CLI
  • Ways to create a deploy
  • netlify.toml deploy contexts
  • Deploy Previews & branch deploys
  • Locking, skipping, and manual production deploys
  • Managing deploys
  • Deploy to Netlify button
  • Secrets scanning failures
  • Fixing a failed deploy — no rollbacks
  • Deploy permissions (private repos)
  • Constraints & gotchas
  • Netlify house rules (deploy)

netlify/netlify-edge-functions

Catalog entry: Skills by Netlify Team
Source documentation: https://github.com/netlify/context-and-tools/blob/main/skills/netlify-edge-functions/SKILL.md

Function: Low-latency edge middleware and geolocation logic

When to use it: use it when an edge function silently does nothing, runs in the wrong order, ignores its Cache-Control headers, or cannot read an environment variable.

Usage guidance is taken from the skill’s own trigger description or usage section.

Source skill menu:

  • Netlify Edge Functions
  • Use this form
  • ⚠️ Footguns
  • Files
  • Return values
  • Endpoint
  • Redirect / rewrite
  • Middleware (modify origin response)
  • Conditional requests
  • Read body, then continue
  • Netlify user gate (private / team-login-protected projects)
  • Post-response work
  • Streaming SSR (`.tsx`)
  • `Context`
  • Declarations
  • Inline `config`

netlify/netlify-forms

Catalog entry: Skills by Netlify Team
Source documentation: https://github.com/netlify/context-and-tools/blob/main/skills/netlify-forms/SKILL.md

Function: HTML form handling with spam filtering

When to use it: Use when adding a contact form, lead-capture form, file-upload form, or newsletter signup to a Netlify site; wiring AJAX form submission; setting up a custom thank-you page; adding a honeypot or reCAPTCHA to a form; getting forms working in Next.js, Nuxt, SvelteKit, Astro, or Gatsby; reading form submissions via the Netlify API; setting up submission notifications or ChatGPT automations on form submission events; or debugging missing submissions and forms that silently fail to register.

Usage guidance is taken from the skill’s own trigger description or usage section.

Source skill menu:

  • Netlify Forms
  • Static HTML form
  • JS-rendered / SSR / framework forms (Next.js, Nuxt, SvelteKit, Astro, Gatsby)
  • AJAX submission
  • File uploads
  • Custom success page
  • Spam prevention
  • Email notifications & subject line
  • Reading submissions via the API
  • Submission summary (field order matters)
  • Debugging missing submissions
  • Constraints
  • Netlify house rules (forms)

netlify/netlify-frameworks

Catalog entry: Skills by Netlify Team
Source documentation: https://github.com/netlify/context-and-tools/blob/main/skills/netlify-frameworks/SKILL.md

Function: Deploy web frameworks with SSR support

When to use it: Use when setting up or fixing a framework deploy (Next.js / Astro / Nuxt / SvelteKit / Remix / React Router / TanStack Start / SolidStart / Gatsby / Angular / Vite / Express / Hydrogen / Hugo / Eleventy / Vue / React), adding SSR or edge functions or middleware wired to Netlify context, fixing SPA redirect and catch-all rules, setting a build command or publish directory, or debugging “why isn’t my env var updating” and framework build failures.

Usage guidance is taken from the skill’s own trigger description or usage section.

Source skill menu:

  • Env vars: modern rules (read first)
  • SPA redirects and the SSR catch-all footgun
  • Local dev with platform emulation (no Netlify CLI)
  • Build settings by framework
  • SSR / adapter setup
  • Astro
  • Next.js (13.5+ only)
  • SvelteKit
  • React Router (7+)
  • Remix
  • Nuxt
  • SolidStart
  • TanStack Start
  • Gatsby
  • Angular
  • Express

netlify/netlify-functions

Catalog entry: Skills by Netlify Team
Source documentation: https://github.com/netlify/context-and-tools/blob/main/skills/netlify-functions/SKILL.md

Function: Build serverless API endpoints and background tasks

When to use it: Writing a REST API endpoint for a static React app without a separate backend Running a background function to process image uploads after the user gets an immediate 202 response Scheduling a nightly cron job to sync data from an external API Streaming server-sent events from a function to a client in real time Accessing geo and IP data from incoming requests to serve localized content

Usage guidance is taken from the skill’s own trigger description or usage section.

Source skill menu:

  • Netlify Functions
  • File locations
  • Minimal function
  • Custom path routing
  • Fetchable module shape (alternative)
  • Context object
  • Who is calling: `context.user`
  • Config object
  • Integrations
  • Streaming responses
  • Background functions (long-running)
  • Scheduled functions (cron)
  • Platform-event functions
  • Region
  • Memory / vCPU
  • Bundling & files on disk

netlify/netlify-image-cdn

Catalog entry: Skills by Netlify Team
Source documentation: https://github.com/netlify/context-and-tools/blob/main/skills/netlify-image-cdn/SKILL.md

Function: Optimize and transform images via CDN

When to use it: Use when adding image optimization or responsive images, converting formats (WebP/AVIF/PNG), generating thumbnails or blur placeholders, serving remote/third-party images through the CDN, allowlisting remote domains in netlify.toml, setting up image redirects or cache headers, building user-uploaded image pipelines, or debugging a 404 on /.netlify/images. Also covers framework image handling for Angular/Astro/Gatsby/Next.js/Nuxt.

Usage guidance is taken from the skill’s own trigger description or usage section.

Source skill menu:

  • Netlify Image CDN
  • Query parameters
  • Common transformations
  • fit behavior
  • Format notes
  • Remote source images
  • remote_images regex escaping
  • Response codes
  • Reusing parameters across images
  • Caching headers
  • Blur placeholders (fm=blurhash)
  • Local development
  • User-uploaded image pipelines
  • Framework image handling
  • Additional constraints
  • Netlify house rules (image-cdn)

NoizAI/skills

Catalog entry: Development and Testing
Source documentation: https://github.com/NoizAI/skills/blob/main/README.md

Function: Human-like TTS workflows with local/cloud APIs and app delivery

When to use it: Use when a task needs the capability described in this catalog entry: Human-like TTS workflows with local/cloud APIs and app delivery

The catalog does not state a separate trigger condition. This usage note is inferred from the published function description.

Source skill menu:

  • Unmute your intelligent bot
  • Install with `npx skills add`
  • Highlights
  • Available skills
  • Quick Verify
  • English Audio Demos
  • Noiz API Key (recommended)
  • Contributing
  • Feedback & Discussion
  • Project Trends
  • GitHub Star Trend
  • Git Clone Trend

This catalog entry points to a collection. The scanned repository lists 10 distinct skill-file paths.

Sample members: characteristic-voice · chat-with-anyone · daily-news-caster · music-video · sound-fx · speech-to-text · template-skill · text-to-music
More members are available in the source repository.

openai/cloudflare-deploy

Catalog entry: Skills by OpenAI
Source documentation: https://github.com/openai/skills/blob/main/skills/.curated/cloudflare-deploy/SKILL.md

Function: Deploy apps to Cloudflare using Workers, Pages, and platform services

When to use it: Use when the user asks to deploy, host, publish, or set up a project on Cloudflare.

Usage guidance is taken from the skill’s own trigger description or usage section.

Source skill menu:

  • Cloudflare Deploy
  • Prerequisites
  • Authentication (Required Before Deploy)
  • Quick Decision Trees
  • “I need to run code”
  • “I need to store data”
  • “I need AI/ML”
  • “I need networking/connectivity”
  • “I need security”
  • “I need media/content”
  • “I need infrastructure-as-code”
  • Product Index
  • Compute & Runtime
  • Storage & Data
  • AI & Machine Learning
  • Networking & Connectivity

openai/render-deploy

Catalog entry: Skills by OpenAI
Source documentation: https://github.com/openai/skills/blob/main/skills/.curated/render-deploy/SKILL.md

Function: Deploy applications to Render’s cloud platform using Git-backed services

When to use it: Use when the user wants to deploy, host, publish, or set up their application on Render’s cloud platform.

Usage guidance is taken from the skill’s own trigger description or usage section.

Source skill menu:

  • Deploy to Render
  • Prerequisites
  • When to Use This Skill
  • Happy Path (New Users)
  • Choose Your Source Path
  • Choose Your Deployment Method (Git Repo)
  • Method Selection Heuristic
  • Prerequisites Check
  • Cursor
  • Claude Code
  • Codex
  • Other Tools
  • Workspace Selection
  • Method 1: Blueprint Deployment (Recommended for Complex Apps)
  • Blueprint Workflow
  • Step 1: Analyze Codebase

openai/vercel-deploy

Catalog entry: Skills by OpenAI
Source documentation: https://github.com/openai/skills/blob/main/skills/.curated/vercel-deploy/SKILL.md

Function: Deploy applications and websites to Vercel with preview or production options

When to use it: Use when the user requests deployment actions like “deploy my app”, “deploy and give me the link”, “push this live”, or “create a preview deployment”.

Usage guidance is taken from the skill’s own trigger description or usage section.

Source skill menu:

  • Vercel Deploy
  • Prerequisites
  • Quick Start
  • Fallback (No Auth)
  • Production Deploys
  • Output
  • Troubleshooting
  • Escalated Network Access

OptimNow/cloud-finops-skills

Catalog entry: Specialized Domains
Source documentation: https://github.com/OptimNow/cloud-finops-skills/blob/main/skills/cloud-finops/README.md

Function: FinOps knowledge: cloud billing mechanics, commitments, allocation, AI spend

When to use it: Use when a task needs the capability described in this catalog entry: FinOps knowledge: cloud billing mechanics, commitments, allocation, AI spend

The catalog does not state a separate trigger condition. This usage note is inferred from the published function description.

Source skill menu:

  • Moved

posteyai/skills

Catalog entry: Marketing
Source documentation: https://github.com/posteyai/skills/blob/main/README.md

Function: Draft, schedule and publish social posts to nine networks

When to use it: Use when a task needs the capability described in this catalog entry: Draft, schedule and publish social posts to nine networks

The catalog does not state a separate trigger condition. This usage note is inferred from the published function description.

Source skill menu:

  • Postey Skills — MCP Server & AI Agent Skills for Social Media
  • Quick start
  • The Postey MCP server
  • The skill and the server are layers, not alternatives
  • What the skill adds
  • Installation
  • Claude Code (recommended)
  • Grok Build
  • Connect the MCP server
  • Credentials
  • Supported platforms
  • Troubleshooting
  • Links
  • License

This catalog entry points to a collection. The scanned repository lists 16 distinct skill-file paths.

Sample members: postey-analytics · postey-engagement · postey-ideas · postey-ops · postey-teams · postey-video · postey-voice · postey
More members are available in the source repository.

publora/skills

Catalog entry: Marketing
Source documentation: https://github.com/publora/skills/blob/main/README.md

Function: Draft, schedule and publish posts to ten social networks

When to use it: Use when a task needs the capability described in this catalog entry: Draft, schedule and publish posts to ten social networks

The catalog does not state a separate trigger condition. This usage note is inferred from the published function description.

Source skill menu:

  • Publora Skills: post to 10 social networks from your AI agent
  • Install
  • Existing Claude Code connections
  • The 9 skills
  • How it works
  • REST fallback
  • FAQ
  • Contributing
  • Related
  • License

This catalog entry points to a collection. The scanned repository lists 9 distinct skill-file paths.

Sample members: bluesky-post · instagram-post · linkedin-analytics · linkedin-post · social-post · telegram-post · threads-post · tiktok-post
More members are available in the source repository.

redhat/sre-skillpack

Catalog entry: Skills by RedHat
Source documentation: https://catalog.redhat.com/en/ai/skills/detail/agentic-skill-pack-for-site-reliability-engineers

Function: Discover, remediate, and verify CVEs across your RHEL fleet — orchestrating Red Hat Lightspeed and Ansible Automation Platform through a single workflow.

When to use it: Use when a task needs the capability described in this catalog entry: Discover, remediate, and verify CVEs across your RHEL fleet — orchestrating Red Hat Lightspeed and Ansible Automation Platform through a single workflow.

The catalog does not state a separate trigger condition. This usage note is inferred from the published function description.

Source skill menu:

  • Platforms
  • Products & services
  • Try, buy, sell
  • Help
  • About Red Hat Ecosystem Catalog
  • Red Hat legal and privacy links
  • Red Hat legal and privacy links

This catalog entry points to a collection. The scanned repository lists 0 distinct skill-file paths.

No individual SKILL.md was retrieved; this entry is based on the catalog description and available repository README.

rorkai/app-store-connect-cli-skills

Catalog entry: Development and Testing
Source documentation: https://github.com/rorkai/app-store-connect-cli-skills/blob/main/README.md

Function: Automate App Store deployments and management using ASC CLI

When to use it: Use when a task needs the capability described in this catalog entry: Automate App Store deployments and management using ASC CLI

The catalog does not state a separate trigger condition. This usage note is inferred from the published function description.

Source skill menu:

  • ASC CLI skills
  • Installation
  • Claude Code plugin
  • Codex plugin
  • Available Skills
  • asc-cli-usage
  • asc-apple-ads
  • asc-workflow
  • asc-app-create-ui
  • asc-xcode-build
  • asc-ad-hoc-distribution
  • asc-screenshot-resize
  • asc-shots-pipeline
  • asc-release-flow
  • asc-signing-setup
  • asc-id-resolver

This catalog entry points to a collection. The scanned repository lists 26 distinct skill-file paths.

Sample members: asc-ad-hoc-distribution · asc-analytics-reports · asc-app-create-ui · asc-apple-ads · asc-aso-audit · asc-build-lifecycle · asc-cli-usage · asc-crash-triage
More members are available in the source repository.

sujunmin/agy-ppt

Catalog entry: Productivity and Collaboration
Source documentation: https://github.com/sujunmin/agy-ppt/blob/main/skills/agy-ppt/SKILL.md

Function: Generate PowerPoint decks without the AI-slop look, purpose-built for the Antigravity+Kiro+Codex pipeline; GPT image rendering handles dense Traditional Chinese slide text far better than Gemini

When to use it: Use when a task needs the capability described in this catalog entry: Generate PowerPoint decks without the AI-slop look, purpose-built for the Antigravity+Kiro+Codex pipeline; GPT image rendering handles dense Traditional Chinese slide text far better than Gemini

The catalog does not state a separate trigger condition. This usage note is inferred from the published function description.

Source skill menu:

  • AGY PPT Orchestrator
  • 1. 目的
  • 2. 核心設計原則
  • 2.1 單一控制者
  • 2.2 AGY 負責「要做什麼」
  • 2.3 Kiro 負責「如何讓系統做到」
  • 2.4 Codex 只負責圖片
  • 3. OAuth-only 執行原則
  • 4. 固定圖片後端
  • 5. Kiro 呼叫原則
  • 5.1 Kiro Runtime
  • 5.2 正式流程
  • 5.3 Agent selection 與 scope
  • 5.4 Agent scope 是 turn-long invariant
  • 5.5 失敗回報
  • 5.6 Permission boundary

testmu-ai/cicd-pipeline-skill

Catalog entry: Skills by TestMu AI
Source documentation: https://github.com/LambdaTest/agent-skills/blob/main/cicd-pipeline-skill/SKILL.md

Function: Generate CI/CD pipelines for tests on GitHub Actions, Jenkins, GitLab CI, and Azure DevOps

When to use it: Use when user mentions “CI/CD”, “pipeline”, “GitHub Actions”, “Jenkins”, “GitLab CI”. Triggers on: “CI/CD”, “pipeline”, “GitHub Actions”, “Jenkins”, “GitLab CI”, “Azure DevOps”, “automated testing pipeline”.

Usage guidance is taken from the skill’s own trigger description or usage section.

Source skill menu:

  • CI/CD Pipeline Skill
  • Core Patterns
  • GitHub Actions
  • Jenkins (Jenkinsfile)
  • GitLab CI
  • Quick Reference
  • Deep Patterns

tushaarmehtaa/tushar-skills

Catalog entry: Development and Testing
Source documentation: https://github.com/tushaarmehtaa/tushar-skills/blob/main/README.md

Function: 34 workflow skills for deploys, outreach, fundraising, specs, launches

When to use it: Use when a task needs the capability described in this catalog entry: 34 workflow skills for deploys, outreach, fundraising, specs, launches

The catalog does not state a separate trigger condition. This usage note is inferred from the published function description.

Source skill menu:

  • slashskills
  • Agent Skills, not runtime-specific prompts
  • Developer tools
  • Install
  • Claude app
  • Skill catalog
  • Contributing
  • V1 scope
  • License

This catalog entry points to a collection. The scanned repository lists 35 distinct skill-file paths.

Sample members: agent-instructions · ai-cost-audit · ai-product-development · analytics · auth-implementation · changelog · cold-outreach · credit-metering
More members are available in the source repository.

veniceai/venice-crypto-rpc

Catalog entry: Skills by Venice.ai
Source documentation: https://github.com/veniceai/skills/blob/main/skills/venice-crypto-rpc/SKILL.md

Function: JSON-RPC proxying for supported crypto networks

When to use it: Use when a task needs the capability described in this catalog entry: JSON-RPC proxying for supported crypto networks

The catalog does not state a separate trigger condition. This usage note is inferred from the published function description.

Source skill menu:

  • Venice Crypto RPC (JSON-RPC proxy)
  • Supported networks
  • Chain families
  • Send a JSON-RPC request
  • Single call
  • Batch (up to 100 calls)
  • Drop-in with `viem`
  • Pricing
  • Response headers
  • Unsupported methods
  • Idempotency
  • Rate limits and concurrency
  • Errors
  • Patterns

vercel-labs/deploy-to-vercel

Catalog entry: Skills by Vercel Engineering Team
Source documentation: https://github.com/vercel-labs/agent-skills/blob/main/skills/deploy-to-vercel/SKILL.md

Function: Deploy applications and websites to Vercel

When to use it: Use when the user requests deployment actions like “deploy my app”, “deploy and give me the link”, “push this live”, or “create a preview deployment”.

Usage guidance is taken from the skill’s own trigger description or usage section.

Source skill menu:

  • Deploy to Vercel
  • Step 1: Gather Project State
  • Team selection
  • Step 2: Choose a Deploy Method
  • Linked (`.vercel/` exists) + has git remote → Git Push
  • Linked (`.vercel/` exists) + no git remote → `vercel deploy`
  • Not linked + CLI is authenticated → Link first, then deploy
  • Not linked + CLI not authenticated → Install, auth, link, deploy
  • No-Auth Fallback — `vercel deploy --temporary`
  • Agent-Specific Notes
  • Claude Code / terminal-based agents
  • Sandboxed environments (claude.ai, Codex)
  • Output
  • Troubleshooting
  • Network Egress Error (claude.ai)
  • Escalated Network Access (Codex / sandboxed environments)

vmware-skills/VMware-AIops

Catalog entry: Specialized Domains
Source documentation: https://github.com/vmware-skills/VMware-AIops/blob/main/skills/vmware-aiops/SKILL.md

Function: AI-powered VMware vCenter/ESXi monitoring and operations: inventory queries, health/alarms, VM lifecycle (create, delete, snapshot, clone, migrate), vSAN management, Aria Operations analytics, and scheduled log scanning. Supports Claude Code, Gemini CLI, Codex, Aider, Trae, Kimi, and MCP.

When to use it: Use this skill whenever the user needs to manage VMs in VMware/vSphere/ESXi — it’s the entry point for all VM operations. Directly handles: power on/off, clone, snapshot, migrate, deploy from OVA or templates, run commands inside VMs, batch operations, cluster management, vCenter alarm acknowledgment, a one-glance cluster-health triage (“is anything on fire?”), and VM/host/datastore investigation drill-downs. Always use this skill for any “power on”, “clone”, “deploy”, “migrate”, “batch”, “guest exec”, “alarm”, or VM lifecycle task, and for triage like “is anything on fire” / “what needs attention now” / “investi

Usage guidance is taken from the skill’s own trigger description or usage section.

Source skill menu:

  • VMware AIops
  • What This Skill Does
  • Audit & Safety
  • Quick Install
  • VMware Family — Install What You Need
  • When to Use This Skill
  • Related Skills — Skill Routing
  • Common Workflows
  • Cluster Health Triage (“what’s wrong right now?”)
  • Object-Centered Investigation → Act (drill-down before you change anything)
  • Deploy a Lab Environment
  • Batch Clone for Testing
  • Migrate VM to Another Host
  • Usage Mode
  • MCP Tools (61 — 18 read, 43 write)
  • CLI Quick Reference

wanshuiyin/Auto-claude-code-research-in-sleep

Catalog entry: Specialized Domains
Source documentation: https://github.com/wanshuiyin/Auto-claude-code-research-in-sleep/blob/main/README.md

Function: Autonomous ML research with cross-model review loops and GPU deployment

When to use it: Use when a task needs the capability described in this catalog entry: Autonomous ML research with cross-model review loops and GPU deployment

The catalog does not state a separate trigger condition. This usage note is inferred from the published function description.

Source skill menu:

  • Auto-claude-code-research-in-sleep (ARIS ⚔️🌙)
  • Contents
  • 1. 🎯 More Than Just a Prompt
  • 2. 📢 What’s New
  • 3. 🚀 Quick Start
  • 4. ✨ Features
  • 5. 📈 Score Progression (Real Run)
  • 6. 🏆 Community Showcase — Papers Built with ARIS
  • 7. 🧩 Awesome Community Skills & Extensions
  • 8. 🔄 Workflows
  • Full Pipeline 🚀
  • Workflow 1: Idea Discovery & Method Refinement 🔍
  • Workflow 1.5: Experiment Bridge 🔗
  • Workflow 2: Auto Research Loop 🔁 (sleep & wake up to results)
  • Workflow 3: Paper Writing Pipeline 📝
  • Workflow 4: Rebuttal 📝 (reply to reviewers safely)

This catalog entry points to a collection. The scanned repository lists 87 distinct skill-file paths.

Sample members: ablation-planner · alphaxiv · analyze-results · arxiv · auto-paper-improvement-loop · auto-review-loop-llm · auto-review-loop-minimax · auto-review-loop
More members are available in the source repository.

Xquik-dev/tweetclaw

Catalog entry: Marketing
Source documentation: https://github.com/Xquik-dev/tweetclaw/blob/master/skills/tweetclaw/SKILL.md

Function: Post tweets, replies, DMs; search, monitor, run giveaways

When to use it: Use when a task needs the capability described in this catalog entry: Post tweets, replies, DMs; search, monitor, run giveaways

The catalog does not state a separate trigger condition. This usage note is inferred from the published function description.

Source skill menu:

  • TweetClaw
  • Install
  • Trust profile
  • Safety rules
  • Pricing
  • Documentation
  • Use TweetClaw for
  • Configure
  • Tools
  • `explore`
  • `tweetclaw`
  • Commands
  • Events
  • Workflow map
  • Read data
  • Security boundaries

zxkane/aws-skills

Catalog entry: Development and Testing
Source documentation: https://github.com/zxkane/aws-skills/blob/main/README.md

Function: AWS development with infrastructure automation and cloud architecture patterns

When to use it: Use when a task needs the capability described in this catalog entry: AWS development with infrastructure automation and cloud architecture patterns

The catalog does not state a separate trigger condition. This usage note is inferred from the published function description.

Source skill menu:

  • AWS Skills for Claude Code
  • Plugins
  • 0. AWS Common Plugin (Dependency)
  • 1. AWS CDK Plugin
  • 2. AWS Cost & Operations Plugin
  • 3. AWS Serverless & Event-Driven Architecture Plugin
  • 4. AWS Agentic AI Plugin
  • Installation
  • Option 1: Claude Code Plugin Marketplace
  • Option 2: Install Individual Skills via npx
  • Core CDK Principles
  • Resource Naming
  • Lambda Functions
  • Pre-Deployment Validation
  • Usage Examples
  • CDK Development

This catalog entry points to a collection. The scanned repository lists 6 distinct skill-file paths.

Sample members: aws-agentic-ai · aws-mcp-setup · aws-cost-operations · aws-cdk-development · aws-sst-development · aws-serverless-eda

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