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.
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sox-testing
by anthropicsGenerate SOX sample selections, testing workpapers, and control assessments. Use when planning quarterly or annual SOX 404 testing, pulling a sample for a control (revenue, P2P, ITGC, close), building a testing workpaper template, or evaluating and classifying a control deficiency.
saas-revenue-growth-metrics
by deanpetersCalculate SaaS revenue, retention, and growth metrics. Use when diagnosing momentum, churn, expansion, or product-market-fit signals.
provider-billing
by pollinationsQuery billing, usage, credits, and resource deployments across all our cloud and SaaS providers (Azure, AWS, Cloudflare, GCP, Tinybird, Vercel, Stripe, Polar, etc.) via their native CLIs and APIs. Use for any question about provider costs, spend by service/day/month, credit eligibility, invoice totals, which resources are running, or how to deploy/inspect resources. Each provider has a dedicated playbook under `providers/`.
commissaire-aux-comptes
by romainsimonCommissaire aux comptes IA pour l'audit des comptes annuels d'entreprises françaises. Applique la démarche NEP en 7 phases : prise de connaissance, contrôle du FEC, vérification du bilan, du compte de résultat, de la balance, de la liasse fiscale, et contrôles transversaux. Émet une opinion motivée sur la fiabilité des comptes avec rapport structuré. Triggers: audit, commissaire aux comptes, CAC, certification, comptes annuels, validation comptes, révision comptable, statutory audit
comptable
by romainsimonComptabilité, fiscalité et facturation pour entreprises françaises. Gère écritures PCG, déclarations TVA, IS/IR, clôture annuelle, liasse fiscale (2033/2065), FEC, états financiers, et chaîne facturation (mentions obligatoires, numérotation, Factur-X/UBL/CII, plateformes agréées PDP/PA, e-reporting, réforme 2026, PEPPOL). Utiliser dès qu'une question porte sur comptabilité française, TVA, impôts, bilan, compte de résultat, amortissement, PCA, clôture, facture, avoir, devis, acompte, facturation électronique, ou e-invoicing.
syndic
by romainsimonGère un parc de copropriétés en France avec vue portfolio consolidée. Couvre administration, comptabilité (décret 2005, plan comptable copro, 5 annexes), assemblées générales (convocation, PV, notification), appels de fonds, travaux, fournisseurs, recouvrement d'impayés et transition de syndic. Maîtrise les majorités (art. 24, 25, 25-1, 26), le fonds de travaux (art. 14-2), le privilège immobilier (art. 19-2) et l'immatriculation RNC. Intégration Qonto pour le rapprochement bancaire. Utilisé pour toute question liée à la copropriété, au syndic bénévole ou coopératif, aux charges, tantièmes, AG, ou au droit de la copropriété (loi 1965, ALUR, ELAN).
greek-financial-statements
by LeoYeAIGreek financial statement generation — P&L, balance sheets, VAT summaries with EGLS integration. Completeness gates prevent partial outputs.
payroll-gl-reconciliation
by LeoYeAIReconcile payroll processor reports (Gusto, ADP, Paychex, Rippling) to general ledger journal entries in QuickBooks Online, Xero, or other accounting software. Automates journal entry creation from payroll summaries, validates wage/tax/benefit allocations to correct GL accounts, detects variances, and flags discrepancies before month-end close. Produces audit-ready reconciliation workpapers. Use when: reconciling payroll registers to GL, mapping payroll processor exports to chart of accounts, creating payroll journal entries, validating employee benefit deductions, or preparing payroll workpapers. NOT for: payroll processing or running payroll (use your payroll platform), tax filing (W-2, 941), on-chain payroll (use on-chain-payroll), HR onboarding, or benefits enrollment.
revenue-recognition-agent
by LeoYeAIASC 606 / IFRS 15 revenue recognition analysis and compliance for SaaS, services, and multi-element arrangements. Guides the 5-step recognition model, identifies performance obligations, determines transaction prices, allocates revenue across obligations, and tracks deferred/contract revenue. Produces journal entries, deferred revenue schedules, and disclosure checklists for audit-ready financials. Use when: recognizing revenue for contracts with customers, reviewing SaaS subscription treatment, analyzing multi-element bundles, booking deferred revenue, or preparing ASC 606 footnote disclosures. NOT for: tax revenue recognition (different rules), government contracts under ASC 808, or lease accounting (use ASC 842 guidance).
3-statements
by ginlix-aiIntegrated 3-statement financial model: linked income statement, balance sheet, and cash flow
check-model
by ginlix-aiFinancial model audit: structural checks, formula validation, integrity testing
budget-rule-engine
by revfactoryA specialized skill providing systematic government grant/funding budget preparation rules and per-category calculation standards. Used by the budget-designer agent when applying per-category ceilings, calculation basis writing methods, and settlement rules during budget preparation. Automatically applied in contexts such as 'budget preparation rules', 'per-category standards', 'budget ceilings', 'settlement guide', 'matching funds'. However, actual accounting processing and tax filing are outside the scope of this skill.
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.