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Awesome Agent Skills Resources

Source-backed learning hub for agent skills, AI agent workflows, MCP tools, coding agents, agent frameworks, agent evaluation, agent safety, deployment readiness, and rollout playbooks.

This repo is an independent educational/resource guide. It explains how skills fit across Codex, Claude Code, GitHub Copilot, OpenClaw, Hermes, Cursor, Gemini CLI, LangGraph, MCP, evaluation tools, deployment surfaces, and team adoption. The canonical catalog remains agentskillexchange/skills, and Agent Skill Exchange is the public site.

Source labels Companion repo

Star this repo if you want a practical map of agent skills, MCP, coding agents, agent frameworks, evaluation, safety, deployment, and team rollout patterns.

Start Here In 60 Seconds

I want to... Start here
Understand agent skills quickly Agent Skills 101
Compare skills, tools, MCP, agents, and workflows Skills vs Tools vs MCP
Browse the best public entry point Awesome Agent Skills
Build, review, and evaluate a first skill Build, Review, Evaluate Path
Compare Codex, Claude Code, Copilot, Cursor, Gemini, OpenClaw, LangGraph, and MCP Framework Comparison
Find official docs, repos, and source-backed resources Resource Index
Evaluate quality, safety, and rollout readiness Checklists and Templates
Browse the canonical skill catalog agentskillexchange/skills

Pick Your First Path

Visitor Read first Why
New to agent skills Agent Skills 101 Get the concept before choosing tools or frameworks.
Building a first reusable workflow Skill Author Starter Kit Turn one source-backed workflow into a reviewable skill draft.
Comparing runtimes or frameworks Framework Comparison Match Codex, Copilot, Claude Code, Cursor, Gemini, OpenClaw, LangGraph, MCP, and SDK surfaces to the job.
Reviewing skill quality First Skill Review Checklist Check setup, permissions, safety, and verification evidence quickly.
Rolling out with a team Team Evaluation Starter Kit Plan a bounded pilot with owners, risks, and evidence.

What You Can Learn Here

  • What agent skills are and where they fit in the agent ecosystem.
  • How skills differ from tools, MCP servers, runtimes, and workflows.
  • How popular ecosystems approach agent frameworks, multi-agent workflows, RAG agents, agent orchestration, agent evaluation, MCP tools, coding agent skills, and agent safety.
  • How agent ops connects observability, evals, LLM traces, approval workflows, workflow automation, AI workflow automation, model gateways, and rollout evidence.
  • How agent safety review connects prompt injection, tool abuse, secrets, runtime guardrails, red teaming, policy, and governance.
  • How to design source-backed skills with clear setup, permissions, and evidence.
  • How to evaluate skill quality without relying on popularity claims.
  • How teams can pilot agent workflows with sandboxing, approval gates, and rollout checks.
  • Where to find official framework, MCP, safety, observability, and adoption resources.

About This Repo

This is a source-backed educational guide for agent skills and AI agent workflows. It provides learning paths, visual maps, examples, rollout playbooks, evaluation templates, source-labeling guidance, and a curated resource index. It is not a catalog mirror and does not try to track every published skill.

What You'll Find Here

Need Start here
Find the right page quickly Docs Index
Learn the agent skills ecosystem Learning Paths
Follow a structured track Curriculum
Understand terminology Glossary
Design better skills Best-Practices Cookbook
Use short review artifacts Checklists
Compare Codex, Claude Code, GitHub Copilot, OpenClaw, Hermes, Cursor, Gemini CLI, LangChain, LangGraph, MCP, and OpenAI Agents SDK Framework pages
Explore popular agent ecosystems Ecosystems
Plan deployment and runtime hosting Deployment
Design evaluation and benchmark evidence Evaluation
Run skill-backed workflows safely Agent Ops
Review security, policy, and governance Security
Review source-backed resources Resource Index
Evaluate skill quality and agent safety Quality Checklist
Run a bounded rollout Playbooks and Templates

I Want To

Goal Go here
Find the best starting point Docs Index
Understand agent skills Agent Skills 101
Follow a role-based path Curriculum
Learn the vocabulary Glossary
Build a first skill Skill Design Patterns
Compare frameworks Framework Comparison
Explore agent ecosystems Popular Agent Ecosystems
Plan runtime hosting Deployment Overview
Design eval evidence Evaluation Overview
Review agent ops evidence Agent Ops Overview
Review agent safety Agent Safety Review Guide
See workflow stacks Showcase Workflow Stacks
Find official resources Resource Index
Review skill quality Skill Evaluation Basics
Build a skill Skill Author Starter Kit and Cookbook
Run a team pilot Team Evaluation Starter Kit
Browse the canonical catalog Agent Skill Exchange

Use This Repo When

  • You want to understand where agent skills fit across AI agents, coding agents, MCP, Model Context Protocol, Codex, Claude Code, GitHub Copilot, OpenClaw, Hermes Agent, Cursor, Gemini CLI, LangChain, LangGraph, and OpenAI Agents SDK.
  • You need source-backed framework resources, visual maps, examples, skill evaluation templates, agent safety checks, verification guidance, or rollout playbooks.
  • You want representative examples without copying the full catalog.

Do Not Use This Repo For

  • The full skill catalog.
  • The installable skill source of truth.
  • Official vendor claims unless the claim is source-backed.
  • Catalog-wide generated skill dumps.

What This Is

Agent skills are reusable instructions, workflows, and tool-usage patterns that help agents perform repeatable work. A good skill explains when to use a tool, how to set it up, what safety checks matter, and how to verify the result.

This repo helps developers answer four questions:

  • Where do skills fit in the agent stack?
  • Which labs, frameworks, and runtimes support skill-like workflows?
  • How should teams evaluate, write, and verify skills?
  • Where can I find source-backed examples without confusing them for the main ASE catalog?

It covers MCP and the Model Context Protocol, verification, skill evaluation, rollout playbooks, popular agent ecosystems, and practical adoption evidence for teams working with agentic development and operations.

How This Differs From agentskillexchange/skills

Repo Purpose Use it for
agent-skills-resources Companion guide Learning, diagrams, framework links, best practices, and curated examples
agentskillexchange/skills Canonical catalog Actual skill files, generated indexes, categories, verification, and installable entries
agentskillexchange.com Live marketplace Browsing, search, skill pages, industry collections, and creation workflows

Skill Ecosystem Layers

Layer Examples What skills add
Model/provider OpenAI, Anthropic, Google Model-specific setup and constraints
Runtime Codex, Claude Code, GitHub Copilot, OpenClaw, Hermes, Cursor, Gemini CLI Repeatable agent workflows
Framework LangGraph, OpenAI Agents SDK, ADK Orchestration patterns and state
Ecosystem CrewAI, AutoGen, Semantic Kernel, LlamaIndex, Pydantic AI, Haystack, Strands, Agno Agent framework concepts and reusable workflow patterns
Deployment Vercel, Cloudflare Workers, Fly.io, Modal, AWS Bedrock Agents, Azure AI Foundry, Google Vertex AI Agent Builder Hosted runtime, sandbox, secrets, and rollout readiness
Evaluation SWE-bench, GAIA, τ-bench, AgentBench, HELM, Inspect AI, OpenAI Evals, Ragas, DeepEval, Braintrust Benchmarks, task rubrics, regression tests, and evidence bundles
Ops LangSmith, Langfuse, Phoenix, Weave, OpenTelemetry, HumanLayer, Composio, n8n, Zapier, Vercel AI Observability, evals, approvals, automation, gateways, and rollout evidence
Security OWASP LLM Top 10, NIST AI RMF, Guardrails AI, Lakera, promptfoo, garak, PyRIT, LlamaFirewall Prompt injection, red teaming, guardrails, secrets, policy, and governance
Protocol/tooling MCP, CLIs, APIs, browser tools Tool setup, permissions, and usage recipes
Verification tests, scans, traces, approvals Evidence that the workflow worked

Ecosystem Map

flowchart LR
  User["User or team"] --> Runtime["Agent runtime"]
  Runtime --> Framework["Agent framework or coding agent"]
  Framework --> Skills["Skills layer"]
  Skills --> Tools["Tools, APIs, CLIs, MCP servers"]
  Skills --> Context["Memory and context"]
  Skills --> Safety["Verification and guardrails"]
  Skills --> Ops["Schedules, crons, deployments"]
  Safety --> Evidence["Tests, scans, logs, citations"]
  Tools --> Outcome["Repeatable workflow outcome"]
  Evidence --> Outcome
Loading

Quick Paths

Path Start here What to read next
Finding docs quickly Docs Index Navigation Index
New to skills Agent Skills 101 Skills vs Tools vs MCP
Role-based curriculum Curriculum Beginner, Builder, Evaluator, Team Lead
Learning terms Glossary Ecosystem Map
Skimming the ecosystem Awesome Agent Skills Framework Comparison
Exploring popular ecosystems Ecosystems Coverage Matrix
Planning deployment Deployment Provider Matrix
Designing evaluations Evaluation Evaluation Tool Matrix
Running with evidence Agent Ops Rollout Evidence
Reviewing safety Security Security Rollout Checklist
Seeing workflow stacks Showcase Workflow Stacks Case Studies
Building a skill Skill Design Patterns Best-Practices Cookbook
Reviewing a skill quickly First Skill Review Checklist Skill Evaluation Worksheet
Reviewing MCP readiness MCP Tooling Readiness MCP Framework Guide
Comparing frameworks Framework pages resources.json
Choosing a starter path Starter Kits Adoption Matrix
Exploring workflows Workflow pages ASE skill mapping
Applying skills to scenarios Case Studies Generated skill mapping index
Planning adoption Playbooks Adoption Matrix
Running a pilot Evaluation Templates Template Index
Reviewing quality Annotated Examples Quality Checklist
Maintaining resources Freshness Audit Source Labeling
Evaluating trust Security And Permissions Skill Evaluation Basics
Running a short readiness review Checklists Templates
Contributing CONTRIBUTING ASE Create Skill

Framework And Resource Guide

Area Role in the ecosystem Guide
Codex Coding agent and terminal workflow runtime Codex
Claude Code Coding agent with project workflows, tools, and automation Claude Code
GitHub Copilot GitHub-native coding assistant, cloud agent, CLI, SDK, MCP, and skills surface GitHub Copilot
OpenClaw Agent runtime for providers, crons, skills, tools, and channels OpenClaw
Hermes Self-improving agent with skills, memory, and agent-managed workflows Hermes
Cursor IDE agent environment with context, skills, and background agents Cursor
Gemini CLI Open-source terminal agent from Google Gemini
LangChain / LangGraph Agent orchestration and stateful workflow framework LangChain / LangGraph
MCP Protocol for connecting agents to tools and context providers MCP

Popular Ecosystems Coverage

This repo also covers broader agent ecosystems that are not always skill-native but strongly shape reusable agent workflows: CrewAI, AutoGen, Semantic Kernel, LlamaIndex, Pydantic AI, Haystack, Strands Agents, and Agno. See the Coverage Matrix for how they relate to agents, tools, workflows, MCP, memory, evals, observability, guardrails, and approvals.

Deployment And Runtime Coverage

Deployment guidance covers runtime hosting, sandbox and container execution, secrets and environments, and deployment readiness. Ecosystem pages cover Vercel Platform, Cloudflare Workers, Fly.io, Modal, AWS Bedrock Agents, Azure AI Foundry, and Google Vertex AI Agent Builder.

Evaluation And Benchmark Coverage

Evaluation guidance covers benchmark landscape, eval design, regression testing, and evidence capture. Ecosystem pages cover SWE-bench, GAIA, τ-bench, AgentBench, HELM, MLCommons AILuminate, Inspect AI, OpenAI Evals, Ragas, DeepEval, and Braintrust.

Agent Ops Coverage

For team adoption, this repo also covers the operational layer around skills: observability and evals, human approval workflows, workflow automation, model gateways and policy, and rollout evidence. Ecosystem pages cover LangSmith, Langfuse, Arize Phoenix, Weights & Biases Weave, OpenTelemetry GenAI, HumanLayer, Composio, n8n, Zapier, Vercel AI SDK, and Vercel AI Gateway.

Security And Governance Coverage

Security guidance covers agent safety review, prompt injection and tool abuse, data and secrets handling, runtime guardrails, red teaming and evals, and policy and governance. Ecosystem pages cover OWASP LLM Top 10, NIST AI RMF, Guardrails AI, Lakera, promptfoo, garak, PyRIT, and LlamaFirewall.

Source Labels

Every resource in data/resources.json uses one of four labels:

  • Official: vendor or project-owned documentation or repository.
  • Lab: research lab, model provider, or frontier-lab material.
  • Community: useful third-party material that is not official.
  • ASE: Agent Skill Exchange site, repo, data, or documentation.

When a claim is not source-backed, leave it out.

Data Files

  • data/resources.json: structured source list.
  • data/ase-skill-mapping.json: representative ASE skill examples by framework and workflow area.
  • docs-index.md: compact front door for all major docs.
  • learning/: framework-neutral learning paths for agent skills.
  • glossary.md: concise vocabulary for skill design and adoption.
  • cookbook/: practical best-practice recipes and anti-patterns.
  • checklists/: short fillable review artifacts for skills, resources, MCP tooling, team pilots, and permissions.
  • ecosystems/: popular agent ecosystem coverage and comparison.
  • deployment/: runtime hosting, sandboxing, secrets, provider matrix, and deployment readiness guidance.
  • evaluation/: benchmark landscape, eval design, regression testing, and evidence capture guidance.
  • ops/: agent operations guidance for observability, evals, approvals, workflow automation, gateways, and rollout evidence.
  • security/: safety, policy, governance, prompt injection, secrets, guardrails, and red-team guidance.
  • diagrams/: framework-neutral Mermaid diagrams.
  • awesome-agent-skills.md: Awesome-style curated front door for agent skill resources.
  • framework-comparison.md: practical comparison of major skill and agent workflow surfaces.
  • showcase/: real-world workflow stacks that combine frameworks, skills, pilot notes, and verification evidence.
  • generated/resource-index.md: generated resource index grouped by source type, framework, and tag.
  • generated/ase-skill-mapping-index.md: generated representative ASE skill index grouped by workflow and framework.
  • generated/nav-index.md: generated navigation index for learning, cookbook, ecosystem, deployment, evaluation, ops, security, framework, workflow, example, case-study, playbook, checklist, template, diagram, contributing, and maintenance pages.
  • generated/template-index.md: generated index of fillable pilot and review templates.
  • generated/repo-stats.md: generated repository data snapshot.
  • workflows/: visual workflow guides that show how skills fit into practical SRE, security, data, content, and research work.
  • case-studies/: practical scenarios that connect 2-4 existing ASE skills into reviewable workflows.
  • playbooks/: adoption guides for teams evaluating skill-based workflows.
  • starter-kits/: short paths for coding-agent users, MCP users, team evaluators, and skill authors.
  • templates/: fillable worksheets for evaluation, risk review, security review, rollout readiness, and post-pilot review.
  • adoption-matrix.md: lightweight comparison of starting workflows, risk levels, rollout paths, and expected evidence.

Quality Loop

Use the repo as a small maintenance loop:

  1. Add or revise source-backed resources.
  2. Map only existing ASE skill slugs.
  3. Review examples against the quality checklist.
  4. Run validation and freshness checks.
  5. Keep source labels honest when ownership changes.

Validation

python3 scripts/validate-resources.py
python3 scripts/validate-links.py
python3 scripts/audit-freshness.py
python3 scripts/generate-resource-index.py
python3 scripts/generate-skill-mapping-index.py
python3 scripts/generate-nav-index.py
python3 scripts/generate-template-index.py
python3 scripts/generate-repo-stats.py

Roadmap

Near-term improvements:

  1. Keep official resource links fresh.
  2. Add more practical examples for team adoption and rollout evidence.
  3. Expand security, policy, and governance guidance for agent workflows.
  4. Add more completed evaluation examples.
  5. Improve framework, ecosystem, deployment, and evaluation comparison pages as official docs evolve.

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