Explore AI Agent Skills & Claude Prompts
Discover open-source agent skills for Claude Code, Codex, ChatGPT, and any tool that uses SKILL.md.
Enter through keywords, occupations, creators, and GitHub sources to see what kinds of skills are emerging across domains.
Use the same catalog through the API
Connect 381,784 public skills to your own search, analytics, or agent workflow with the REST API.
Querying local SQLite index...
push
by alexandreandreClôture une session Git sur une branche personnelle dev-* : vérifie la branche courante, regroupe ou découpe les commits selon les changements, rédige des messages détaillés et propres, pousse vers origin sur la même branche (jamais main). À utiliser en fin de journée ou de session, lorsque l’utilisateur demande /push, de sauvegarder ou pousser son travail sur sa branche dev, ou attache explicitement ce skill.
test-complet
by alexandreandreÉlabore une matrice exhaustive de scénarios pour une page ou une fonctionnalité, les exécute un par un (code, API, pytest, navigateur si disponible), puis produit un compte rendu structuré en français. À utiliser lorsque l'utilisateur tape /test-complet, demande un test exhaustif, une recette complète, ou une couverture de tous les cas possibles d'un écran ou d'un flux.
frontend-design
by alexandreandreAméliore l’UI/UX du frontend à partir d’une description en langage naturel tout en évitant le rendu générique « fait par IA ». Couvre typographie, couleurs, espacements, états interactifs, responsive, accessibilité et cohérence avec le design system existant. À utiliser lorsque l’utilisateur demande de polir le design, de rendre une page plus professionnelle, d’éviter l’esthétique cliché IA, ou attache explicitement ce skill.
enhance-fonctionnality
by alexandreandreAmeliore une fonctionnalite existante en generant des idees d'amelioration de maniere autonome, puis en les implementant. Couvre UX, robustesse, performance, completude, accessibilite et coherence. A utiliser lorsque l'utilisateur tape /enhance-fonctionnality, demande d'ameliorer une fonctionnalite, de rendre une feature plus complete, plus robuste, ou plus professionnelle, ou attache explicitement ce skill.
plan-page
by alexandreandrePlan d'amélioration d'une page web sous l'œil d'un product manager RH expérimenté. Audite la disposition, l'UI, l'UX et les données affichées, puis produit un plan priorisé (laisser tel quel, ajustements minimes, ou refonte ciblée si la page le mérite). N'implémente rien, ne touche pas au backend, ne supprime rien sans accord. À utiliser lorsque l'utilisateur tape /plan-page, demande un plan pour améliorer une page, une revue UI/UX d'écran, un avis de PM RH sur la disposition d'une page, ou attache explicitement ce skill.
enhance
by alexandreandreBenchmark complet, auto-evaluation et amelioration systematique d'un outil logiciel. Construit un panel de tests couvrant tous les cas d'usage, execute le benchmark, produit un rapport detaille, puis corrige chaque point faible et re-valide. A utiliser lorsque l'utilisateur tape /enhance, demande de tester, benchmarker, evaluer, ameliorer, ou auditer un outil, une API, un pipeline, un CLI, un service, ou tout composant logiciel.
perf-agent
by alexandreandreBrainstorme et priorise des idees d'amelioration des performances (latence, cout, qualite des sorties, fiabilite, scalabilite) pour un agent metier donne parmi prospection, rachat, benchmark, sous-traitant, creation d'entreprise. Couvre architecture, APIs, prompts, donnees, observabilite et tout levier pertinent. A utiliser lorsque l'utilisateur tape /perf-agent, demande des idees de performance pour un agent, ou attache explicitement ce skill.
resume
by alexandreandreRésume en une seule phrase courte ce qui vient d'être implémenté, corrigé ou amélioré (session courante ou changements Git locaux). À utiliser lorsque l'utilisateur demande /resume, une phrase récap, un résumé en une ligne, ou attache explicitement ce skill.
update-copilot-rh
by alexandreandreActualise exhaustivement l'assistant « Demander à l'IA » du tableau de bord RH EYWAI : guide produit (navigation, parcours, actions), schéma Supabase (tables/colonnes/valeurs JSONB), exemples few-shot et règles de promptage. À utiliser lorsque l'utilisateur tape /update-copilot-rh, demande de mettre à jour l'agent IA du dashboard, enrichir le copilot RH, ou synchroniser les connaissances après une nouvelle feature ou migration Supabase.
Browse Agent Skills by Occupation
23 major groups · 867 SOC occupations
Browse by Category
Explore agent skills organized by their primary use case
Explore the agent skills ecosystem by occupation and creator
SkillMD is not just a keyword search box. It is an open map that organizes public skills by occupation, creator, and repository, helping you see which workflows, judgment criteria, and domain habits people are writing for AI agents.
Then follow creators and GitHub repositories back to the source: compare the skills a team maintains, whether the repo is active, and how the README frames the work before you open, install, or reuse anything.
Use it three ways: learn an unfamiliar field by occupation, study how creators organize skills, then use source context to decide what is worth opening or reusing.
01 Map a field
Browse 23 occupation groups and 867 SOC roles to learn what skills exist in adjacent domains and how they break down real work.
02 Follow creators
Use creator and repository pages to inspect maintained skill collections, recent updates, and source context before trusting a result.
03 Search with sources
Search 1.7M+ collected skills, then use occupation tags, creators, and GitHub source context to decide what is worth opening.
Start with the occupation map, then follow creators and repositories back to real code. SkillMD helps explain why a skill is worth opening, not only what it is named.
Standardizing Agent Capabilities with SKILL.md and Model Context Protocol (MCP)
In the rapidly evolving landscape of artificial intelligence, LLM agents (Large Language Model agents) have transitioned from simple text predictors to autonomous problem solvers. To orchestrate complex, multi-step agentic workflows, developers require a standardized format to specify agent capabilities, prompt instructions, system rules, and database bindings. This is where SKILL.md and the Model Context Protocol (MCP) have emerged as standard developer paradigms. SkillMD serves as the central directory for indexing, exploring, and sharing these critical agent configurations.
Our open-source registry currently tracks over 1.7 million collected SKILL.md configurations and system prompts. By compiling agent configurations from active developers on GitHub, we bridge the gap between prompt engineering research and production execution. Whether you are building agents with Anthropic's Claude Code, OpenAI's GPT-4, Google's Gemini, or local models using Ollama and LlamaIndex, standardized skill definitions ensure your agents behave predictably across different runtime environments.
What is the Model Context Protocol (MCP)?
The Model Context Protocol (MCP) is an open-source standard designed to connect LLMs to data sources, developer tools, and external environments. MCP establishes a bidirectional communication channel between client applications (like Cursor, Claude Desktop, or custom agent systems) and servers hosting data or capabilities. Standardizing instructions via SKILL.md enables LLMs to query databases, read local files, execute terminal commands, and integrate third-party APIs. SkillMD allows you to find ready-to-run MCP servers and prompt instructions for various occupations and technical tasks.
The Structure of a Professional SKILL.md File
A valid SKILL.md configuration is designed to be easily read by humans and parsed by LLMs. It contains precise system instructions, trigger conditions, required parameters, and execution examples. Below is the typical architectural blueprint of a professional agent skill:
- Metadata & Core Scope: Declares the name of the skill, author details, target models, and a description of the capability.
- Triggers & Intent Detection: Details semantic triggers that help the agent decide when to invoke this skill.
- System Prompts: Explicit system-level instructions that direct the agent's behavior, personality, safety guardrails, and formatting preferences.
- Capabilities & Tools: Lists the files, databases, or APIs the agent must access to complete the tasks.
- Few-Shot Examples: Demonstrates real inputs and outputs, helping the model generalize behavior through in-context learning.
Optimizing Agent Workflows for Modern LLMs
Writing effective agent skills requires deep knowledge of prompt engineering. With the release of advanced reasoning models like Claude 3.5 Sonnet, ChatGPT o1, and DeepSeek-V3, prompt templates must focus on structured thinking. Developers are encouraged to use XML tags (e.g., <thought>, <context>, and <rules>) to isolate execution boundaries. Standardized prompts prevent agents from suffering from context drift, ensuring that long-running tasks remain aligned with the initial system parameters.
Exploring by SOC Occupations and Creator Profiles
What makes SkillMD unique is its taxonomy. Instead of simple text search, we parse and organize files according to the Standard Occupational Classification (SOC) system. This means you can discover skills written for Computer and Mathematical roles, Business and Financial operations, Legal, Design, and and Educational Instruction fields. By tracking creator profiles, developers can study how different teams organize their custom instructions, compare version updates, and fork public configs for specialized enterprise use cases.
SkillMD operates as a high-performance index running on a fast Go backend and a highly responsive Astro SSR frontend. All search queries execute in milliseconds, featuring smart debouncing to prevent multiple API requests while keeping user data secure. Join our community of developers to standardize your AI agent instructions and optimize your LLM prompting workflows today.
Frequently Asked Questions
A practical guide to agent skills: what they are, how to inspect them, and how SkillMD helps you explore the ecosystem.