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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bitterpillengineering
by danielmiesslerAudits any AI instruction set for over-prompting using the core test: would a smarter model make this rule unnecessary? Applies Five Questions to every rule — Does Claude already do this? Contradiction? Redundant? One-off fix? Vague? — then classifies each as CUT / RESOLVE / MERGE / EVALUATE / SHARPEN / MOVE / KEEP. Two workflows: Audit (full system — reads all force-loaded files from settings.json, reports token savings estimate) and QuickCheck (single file, fast keep/cut/sharpen verdict). Outputs categorized report with estimated line and token savings. Core principle: less scaffolding = better output — every unnecessary rule competes for attention and degrades the rules that matter. Anti-fragile rules to KEEP: verification harnesses, ISC, data pipelines, specific DO/DON'T examples, tool preferences, routing rules. Fragile rules to CUT: CoT orchestrators, format parsers, retry cascades, numeric personality scales, abstract value statements. Requires loadAtStartup and postCompactRestore.fullFiles to stay in
becreative
by danielmiesslerDivergent ideation and corpus expansion using Verbalized Sampling + extended thinking. Single-shot mode generates 5 internally diverse candidates (p<0.10 each) and surfaces the strongest. Multi-turn mode expands a small seed corpus (5-20 examples) into a diverse N-example dataset for evals, training, or test sets. Research-backed: Zhang et al. 2025 (arXiv:2510.01171) — 1.6-2.1x diversity increase on creative writing, 25.7% quality improvement, and synthetic-data downstream accuracy lift 30.6% → 37.5% on math benchmarks. Seven workflows: StandardCreativity, MaximumCreativity, IdeaGeneration, TreeOfThoughts, DomainSpecific, TechnicalCreativityGemini3 for algorithmic/architecture work, and SyntheticDataExpansion for VS-Multi corpus growth. Single-shot output is one best response, not a ranked list; SyntheticDataExpansion writes a JSONL corpus to MEMORY/WORK/{slug}/synthetic-data/. Integrates with XPost, LinkedInPost, Blogging (creative angles), Art (diverse image prompt ideas), Business (offer frameworks), Resea
becreative
by danielmiesslerDivergent ideation via Verbalized Sampling + extended thinking (1.6-2.1x diversity). USE WHEN be creative, deep thinking, brainstorm, divergent ideas, creative solutions, maximum creativity, tree of thoughts, idea generation, domain specific creativity, technical creativity, standard creativity.
brightdata
by danielmiessler4-tier progressive URL scraping and multi-page crawling — WebFetch, then Chrome-header curl, then Playwright browser, then Bright Data proxy. Auto-escalates when lower tiers fail. USE WHEN Bright Data, scrape URL, web scraping, site blocking me, can't access, bot detection, crawl site, crawl pages, spider, CAPTCHA, four tier scrape, progressive scraping, Chrome headers.
becreative
by danielmiesslerDivergent ideation via Verbalized Sampling + extended thinking (1.6-2.1x diversity). USE WHEN be creative, deep thinking, brainstorm, divergent ideas, creative solutions, maximum creativity, tree of thoughts, idea generation, domain specific creativity, technical creativity, standard creativity.
brightdata
by danielmiessler4-tier progressive scraping with automatic escalation: Tier 1 WebFetch (fast, built-in), Tier 2 curl with Chrome headers (basic bot bypass), Tier 3 agent-browser (headless JavaScript rendering via Rust CLI daemon), Tier 4 Bright Data MCP proxy (CAPTCHA, advanced bot detection, residential proxies). Two workflows: FourTierScrape for single URLs, Crawl for multi-page site mapping (light crawl via scrape_batch loop up to 50 pages, or full crawl via Bright Data Crawl API). Always starts at Tier 1 and escalates only when blocked — Tier 4 has usage costs. Outputs URL content in markdown format. USE WHEN Bright Data, scrape URL, web scraping, bot detection, crawl site, CAPTCHA, can't access, site blocking, extract page content, scrape whole site, spider domain, convert URL to markdown, getting blocked. NOT FOR headless batch automation without scraping need (use Browser). NOT FOR simple public content (use WebFetch directly). NOT FOR real-browser bot bypass where staying logged in and zero CDP fingerprint matter (us
daemon
by danielmiesslerManage the public daemon profile — a living digital representation of what you're working on, thinking about, reading, and building. DaemonAggregator.ts reads PAI sources (TELOS missions/goals/books/wisdom, KNOWLEDGE/Ideas titles, PROJECTS.md, MEMORY/WORK themes, PRINCIPAL_IDENTITY bio) and writes to daemon-data.json. SecurityFilter.ts applies deterministic pattern-matching (NOT LLM judgment) to strip names, paths, credentials, and internal refs. Structurally excludes CONTACTS, FINANCES, HEALTH, OUR_STORY, OPINIONS. deploy.sh builds the VitePress static site and deploys to Cloudflare Pages. Two-repo pattern: public framework (danielmiessler/Daemon, forkable) + private content (daemon-dm). Workflows: UpdateDaemon, ReadDaemon, PreviewDaemon, DeployDaemon. USE WHEN daemon, update daemon, daemon profile, deploy daemon, preview daemon, read daemon, check daemon, daemon status, public profile, digital presence. NOT FOR internal PAI system management (use _PAI).
documents
by danielmiesslerRead, write, convert, and analyze documents — routes to PDF, DOCX, XLSX, PPTX sub-skills for creation, editing, extraction, and format conversion. USE WHEN document, process file, create document, convert format, extract text, PDF, DOCX, XLSX, PPTX, Word, Excel, spreadsheet, PowerPoint, presentation, slides, consulting report, large PDF, merge PDF, fill form, tracked changes, redlining.
evals
by danielmiesslerObjective eval metrics via code/model/human graders with pass@k/pass^k scoring. USE WHEN eval, evaluate, test agent, benchmark, verify behavior, regression test, capability test, run eval, compare models, compare prompts, create judge, create use case, view results, failure to task, suite manager, transcript capture, trial runner.
extractwisdom
by danielmiesslerContent-adaptive wisdom extraction — detects what domains exist in content and builds custom sections (not static IDEAS/QUOTES). Produces tailored insight reports from videos, podcasts, articles. USE WHEN extract wisdom, analyze video, analyze podcast, extract insights, what's interesting, extract from YouTube, what did I miss, key takeaways.
evals
by danielmiesslerComprehensive AI agent evaluation framework with three grader types (code-based: deterministic/fast; model-based: nuanced/LLM rubric; human: gold standard) and pass@k / pass^k scoring. Evaluates agent transcripts, tool-call sequences, and multi-turn conversations — not just single outputs. Supports capability evals (~70% pass target) and regression evals (~99% pass target). Workflows: RunEval, CompareModels, ComparePrompts, CreateJudge, CreateUseCase, RunScenario, CreateScenario, ViewResults. Integrates with THE ALGORITHM ISC rows for automated verification. Domain patterns pre-configured for coding, conversational, research, and computer-use agent types in Data/DomainPatterns.yaml. Tools: AlgorithmBridge.ts (ISC integration), FailureToTask.ts (failures → tasks), SuiteManager.ts (create/graduate/saturation-check), ScenarioRunner.ts (multi-turn simulated-user), TranscriptCapture.ts, PAIAgentAdapter.ts (wraps Inference.ts), ScenarioToTranscript.ts. Code-based graders: string_match, regex_match, binary_tests, st
extractwisdom
by danielmiesslerContent-adaptive wisdom extraction that reads the content first, detects what wisdom domains are actually present, then builds custom sections around what it finds — instead of forcing static headers every time. A security talk gets 'Threat Model Insights' and 'Defense Strategies'; a business podcast gets 'Contrarian Business Takes' and 'Money Philosophy'. Five depth levels: Instant (1 section), Fast (3 sections), Basic (3+takeaway), Full (5-12 sections, default), Comprehensive (10-15+themes). Voice follows the user's conversational style — bullets read like telling a friend what you just watched, not a press release. Output always includes dynamic sections, One-Sentence Takeaway, 'If You Only Have 2 Minutes', and References. Spicy/contrarian takes are mandatory inclusions, never softened. YouTube content extracted via `fabric -y URL` before extraction; article content fetched via WebFetch. Output: markdown with dynamic section headers, closing sections vary by depth level, References & Rabbit Holes, optional
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.