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.
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recovery-and-setbacks
by kvmaddenUse this skill the moment the operator is processing a setback, failure, rejection, or recovery — public or private, work or personal, immediate or delayed. Triggers include phrases like "I failed at", "didn't follow through on", "it bombed", "no one used it", "the launch failed", "got dragged on [platform]", "they said no", "I didn't get it", "got rejected", "they passed", "I committed to too much", "I'm drowning", "everything's piling up", "I dread", "what's the point", "everything feels hard", "running on empty", "I don't care anymore", "I'm anxious about money", "money is making me weird", "I keep avoiding looking at finances", or signals of fear-driven stuck-ness ("I don't know why I keep stalling", "I should just do this but...", "I keep avoiding", "I'm not sure why this is hard"). Apply even when the operator hasn't asked for help — naming the recovery pattern is often the value, more than prescribing. Consult the skill's rules/ folder to identify the specific recovery shape (burnout, overcommitment, p
self-watch
by kvmaddenUse this skill whenever the operator names an inner-state pattern that benefits from a soft observation — boredom (different from stuck or tired), hiding (high activity without exposure), procrastinating (pivoting to easier work mid-hard-task), stuck on a problem that's a symptom of a layer-up problem, fun / useful conflation hiding real motivation, urge to add more inputs when sitting with what you have would beat more research, 30+ min stuck + no body break, real win that just landed and the operator is pivoting to "what's next" without acknowledging, body / personal-maintenance signals deferred under task-focus, reading-aspirations mentioned without capture. Triggers include "I'm not feeling it", "this is dragging", "I keep zoning out", "I'm fried", "exhausted", "wired but tired" (am-i-bored / body-and-maintenance); "I've been working on this forever" + low exposure signals (am-i-hiding); "I'm stuck", "I keep doing X but", "I should be doing Y but", "let me clean up instead", "I'm just going to refactor" (
claude-quality-watch
by kvmaddenUse this skill whenever Claude's own output starts drifting in ways that corrode session value — sycophancy (3+ agreements without pushback), paraphrase drift (paraphrasing what the operator said with added content they didn't say), hallucinated code (generated code referencing APIs / libraries / signatures that don't exist), confident factual claims about current state without fresh verification (claims about file contents, function names, API behavior, package versions, endpoint shapes — all checkable but unchecked), stale current-state claims (saying "currently X" without fresh verification), direction-by-momentum (the operator nodding along to a path Claude pushed confidently), skim-and-trust on long Claude outputs (rapid "looks good" / "ship it" within seconds of a 200+ line output), or whenever the operator pushes back with phrases like "no, that's not what I meant", "I didn't say that", "wait, how did we end up here", "I don't think this was my idea", "you're misreading me". Also trigger preventively e
claude-effective-usage
by kvmaddenUse this skill whenever the operator could work with Claude more effectively — by picking the right surface, the right tool tier, or the right session hygiene. Three families: (1) RIGHT SURFACE — choosing among Claude Code / Chat / Cowork / Dispatch. Triggers like "by EOD", "have this ready when I get back", "investigate X and report", "go gather all the Y and summarize" (async multi-step → Dispatch); "brainstorm with me", "what do you think of", "help me think through", "think out loud" (open exploration → Chat); "draft a proposal", "write the brief", "compose an email", "I need a spec doc" (document drafting → Cowork). (2) TOOL-TIER EFFICIENCY — about to use computer-use / screenshots when a dedicated app MCP exists; about to poll or sleep-loop for a condition that could be event-driven; about to make several independent tool calls sequentially when they could run in parallel in one message; a bounded task that maps to a specialized agent or a codebase-wide search. (3) SESSION HYGIENE — "save this" / "remem
cadence-review
by kvmaddenUse this skill whenever the operator is in a day-, week-, or quarter-lifecycle rhythm moment that benefits from an explicit review or check above the immediate work. Triggers include: "shape the day", "day-shape", "what's today's plan", morning of a working day, drift-check cadence every 2-3h (day-shape); a real deadline being mentioned — "due Friday", "by EOD", "before the meeting", "I told my ${user_config.manager_title} I'd send by tomorrow", "1on1 in 2 hours", any explicit date / time commitment (deadline-lock); "I'll dedicate a full Saturday", "when I have a free weekend", "haven't worked on X in 3 weeks but I'll catch up" (daily-practice — frequency beats intensity); "show me the pattern", "where did time go", "pattern report", "what did this week look like", "effort breakdown", weekly cadence (first session of Sunday post-zoom-out) (pattern-report); post-pattern-report cadence with accumulated long-session data (first-hour-vs-last-hour — quality curve so hardest work routes to front); "zoom out", "step
accidental-phi
by kvmaddenHARD STOP. Use this skill the moment any text in the conversation looks like it could be Protected Health Information (PHI) from a healthcare context the operator works in. This is the HIGHEST-PRIORITY skill in the plugin — it fires before everything else, suppresses other skills firing same turn, and has NO override for "trust me it's not PHI" without explicit confirmation. Triggers include: any phone-shaped string `\b\d{3}[-.\s]?\d{3}[-.\s]?\d{4}\b`, SSN-shaped string `\b\d{3}[-]\d{2}[-]\d{4}\b`, DOB-shaped MM/DD/YYYY pattern, Rx number `\bRx\s*#?\s*\d{6,}\b`, MRN `\bMRN\s*#?\s*\d+\b`, any `<title> <first-name> <last-name>` pattern in a healthcare context document (Mrs. Mary Smith, Dr. James Lee, Mr./Ms.), or the word "patient" appearing alongside any number / identifier / clinical detail. Also fires on file paths or pastes containing patient / Rx / script / MRN / EHR / clinical / `<employer>-internal` markers. When fired, REFUSE to write the data, REFUSE to log it anywhere (persistent store, chat output, B
cognitive-distortion-watch
by kvmaddenUse this skill whenever the operator uses self-talk that contains a cognitive-distortion pattern — binary framing of gradient situations, categorical self-statements, external comparisons, mind-reading about others' mental state, borrowed "shoulds", or sunk-cost reasoning (continuing because of past investment rather than forward value). Triggers include phrases like "I always", "I never", "I'm just not the kind of person who", "I can't ever", "I'm either X or Y", "all or nothing", "100% or 0%", "compared to [X]", "[Person] is doing", "I'm behind", "people my age", "they think", "she's mad", "he wants", "I should do X", "I should be working on Y", "I should have", "I've already built half of it", "I've put X hours in", "I'm too far in", "I might as well finish", "I can't waste what I've already done", "after all this work", or similar self-talk where the operator's framing is distorted. Apply even when the operator hasn't asked for a check — naming the distortion at the moment is the value, even mid-flow. Con
Browse Agent Skills by Occupation
23 major groups · 867 SOC occupations
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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.