381,784 Collected SKILL.md files

Explore AI Agent Skills & Claude Prompts

Discover open-source agent skills for Claude Code, Codex, ChatGPT, and any tool that uses SKILL.md.

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Showing 12 of 14 skills
mhylle

iterate-plan

by mhylle
star 16

Update existing implementation plans through user feedback with thorough research and validation. Also migrates old checkbox-based plans to the new Task tools system. This skill should be used when iterating on implementation plans, updating plans based on new requirements, refining technical approaches in existing plans, migrating old plans to Task tools, or when the user wants to modify a previously created plan file. Triggers on requests like "update the plan", "change the implementation approach", "iterate on this plan", "migrate to new system", or when feedback is provided about an existing plan document.

navigation main article SKILL.md
schedule Updated 5 months ago
mhylle

tt-implement-plan

by mhylle
star 16

Tasktracker-native plan orchestrator. Drives execution of a plan whose phases are stored as tasktracker phase tasks (NOT a docs/plans/*.md file). Honours active-task discipline (setActiveTask before every artifact-producing call, pauseActiveTask before user waits, clearActiveTask on phase done), respects the locked phase body (design notes go to sub-tasks, never to the phase description), logs defects/learnings/frictions through tasktracker insights as they surface, and delegates the actual implementation to /implement-phase. Use whenever the user wants to "implement the plan", "run the plan", or "work through the phases" AND the plan was created with /tt-create-plan (or otherwise lives in tasktracker). Triggers on "tt implement plan", "tt implement", "implement plan (tasktracker)", "/tt-implement-plan", "execute the tasktracker plan", or any plan-execution request inside a session that already has a tasktracker active task or project. Prefer this over the plain /implement-plan skill whenever a tasktracker MC

navigation main article SKILL.md
schedule Updated 23 days ago
mhylle

tt-workflow-audit

by mhylle
star 16

Tasktracker-native project-wide parallel audit using the Claude Code Workflow tool (dynamic workflows). Partitions a repo / backlog / architecture and fans out read-only agents (one per partition) that return schema-checked findings, aggregates them into a deduplicated, ranked risk register, and OPTIONALLY writes fixes back as tasks under a Bug Fix phase — with all tasktracker writes done by the PARENT, never the parallel agents (single global active-task pointer). Journaled and resumable, so a rate-limit or crash mid-audit resumes without re-running completed partitions. Use for large, embarrassingly-parallel, read/analyze-heavy jobs where each unit is self-contained and the output aggregates — audit every file/component for risk, find all architecture drift (scanArchitectureDrift) or duplicate tasks (detectDuplicates/auditDuplicates), per-file tech-debt sweep, test-coverage or security-surface scan across a whole project. Triggers on "/tt-workflow-audit", "audit the whole repo", "parallel audit", "scan ever

navigation main article SKILL.md
schedule Updated 23 days ago
mhylle

tt-workflow-build

by mhylle
star 16

Tasktracker-native trigger for a PARALLEL build via the Claude Code Workflow tool. Thin by design — it does two things, then drives to done: (1) ensure a tasktracker project exists (use the existing one, or create one), then (2) start a dynamic `Workflow` that builds it, tracking the work in tasktracker and using the build + verify skills. It does NOT analyze parallelism up front, ask the user to choose a mode, hand back, or fall back to a sequential skill — get a project, start the workflow, drive autonomously to done (pausing only at real human gates like deploy). Use when the user wants a build driven by the parallel Workflow engine — typically after /tt-brainstorm + /tt-create-plan, or standalone. Triggers on "/tt-workflow-build", "build this with a workflow", "parallel build (tasktracker)", "fan out the build". Prefer /tt-implement-plan or /tt-workflow-run only when the WHOLE job is irreducibly sequential; prefer /tt-workflow-audit for read-only analysis.

navigation main article SKILL.md
schedule Updated 23 days ago
mhylle

tt-brainstorm

by mhylle
star 16

Tasktracker-native Socratic brainstorming. Refines a raw idea into a frozen brainstorm document tree stored in tasktracker (NOT in docs/brainstorms/*.md), with every chosen/deferred/rejected option recorded as a decision and an optional one-way promotion into a task tree. Use whenever a user wants to brainstorm, explore, refine, or "think through" an idea AND the work is (or will be) tracked in tasktracker. Triggers on "tt brainstorm", "brainstorm with tasktracker", "brainstorm in tasktracker", "explore this idea (tasktracker)", "/tt-brainstorm", or any brainstorm-style request inside a session that already has a tasktracker active task or project. Prefer this over the plain /brainstorm skill whenever a tasktracker MCP is available — the artifacts integrate with /tt-create-plan and /tt-implement-plan, so picking the file-based variant in a tasktracker project just creates orphan markdown.

navigation main article SKILL.md
schedule Updated 23 days ago
mhylle

tt-create-plan

by mhylle
star 16

Tasktracker-native implementation planning. Turns a frozen brainstorm (or a clear requirement) into a phased plan persisted as tasktracker phase tasks — NOT as a docs/plans/*.md file. Creates requirements with formal acceptance criteria, registers architecture components, generates phases via createPhaseFromTemplate (backend-feature / ui-fix / refactor / schema-migration / bug-investigation / docs-only / data-housekeeping), links every task back to its requirement, and uses getProjectReadiness as the completion gate. Use whenever the user wants to plan, design, or scope an implementation AND the work is (or will be) tracked in tasktracker. Triggers on "tt create plan", "tt plan", "plan this in tasktracker", "create a plan (tasktracker)", "/tt-create-plan", or any plan-creation request inside a session that already has a tasktracker active task or project. Prefer this over the plain /create-plan skill whenever a tasktracker MCP is available — the resulting phase tasks integrate with /tt-implement-plan and /imp

navigation main article SKILL.md
schedule Updated 29 days ago
mhylle

tt-implement-phase

by mhylle
star 16

Tasktracker-native per-phase executor. Runs a SINGLE phase whose scope and sub-tasks live as tasktracker phase + sub-task rows (NOT in a docs/plans/*.md file). Honours active-task discipline (setActiveTask on phase AND on each sub-task as worked), respects the locked phase body (HTTP 422 on description edit — design notes go to sub-tasks), updates sub-task status via tasktracker_updateTaskStatus as work progresses, logs defects/learnings/frictions through tasktracker insights, and delegates code work to subagents when a subagent-dispatch tool is available — otherwise does the work in-context itself (graceful degradation), never stalling. Used by /tt-implement-plan as the per-phase unit of work; can also be invoked directly with a phase task id. Triggers when /tt-implement-plan delegates a phase, or manually with "/tt-implement-phase <phase-task-id>", "tt implement phase", "execute phase (tasktracker)", "/tt-implement-phase". Prefer this over the plain /implement-phase skill whenever a tasktracker MCP is avail

navigation main article SKILL.md
schedule Updated 23 days ago
mhylle

brainstorm

by mhylle
star 15

Interactive idea refinement using Socratic questioning methodology. This skill should be used when users want to explore an idea, find gaps in concepts, enhance proposals, or structure thoughts before implementation planning. Triggers on "brainstorm", "explore this idea", "find holes in", "help me think through", "what am I missing", or when presenting rough concepts that need refinement. Output integrates with create-plan skill.

navigation main article SKILL.md
schedule Updated 3 months ago
mhylle

implement-plan

by mhylle
star 15

Orchestrate the execution of complete implementation plans, delegating each phase to implement-phase skill. This skill manages the full plan lifecycle including phase sequencing, user confirmation between phases, and overall progress tracking. Triggers on "implement the plan", "execute the implementation plan", or when given a path to a plan file.

navigation main article SKILL.md
schedule Updated 4 months ago
mhylle

team-brainstorm

by mhylle
star 15

Adversarial brainstorming using agent teams for multi-perspective analysis. Use when users want thorough idea exploration with real debate between independent perspectives. Triggers on "team brainstorm", "adversarial brainstorm", "brainstorm with team", "debate this idea", or when the user explicitly requests team-based analysis. Higher token cost but significantly deeper analysis than single-agent brainstorm.

navigation main article SKILL.md
schedule Updated 3 months ago
mhylle

deep-brainstorm

by mhylle
star 15

Multi-session, resumable deep brainstorming with mindmap-on-disk structure. Explores ideas across multiple dimensions using creative methodologies (Morphological Analysis, TRIZ, Lateral Thinking, Lotus Blossom, Assumption Mapping). Sessions persist to filesystem and can span days. Triggers on "deep brainstorm", "deep dive brainstorm", "multi-session brainstorm", "brainstorm deeply", or when the user wants extended, resumable idea exploration. Higher depth than brainstorm or team-brainstorm but spread across sessions.

navigation main article SKILL.md
schedule Updated 3 months ago
mhylle

strategic-compact

by mhylle
star 15

Suggest context compaction at optimal logical boundaries — between phases, after a research burst, after a debugging session ends — rather than waiting for the automatic compaction threshold to hit mid-task. Use when the user asks whether to compact, mentions context is getting long, wants to checkpoint before a big task, or when you notice the session is approaching a natural transition where compacting would preserve the next phase's context. Complements (doesn't replace) Claude Code's built-in auto-compaction. Triggers on "/strategic-compact", "should I compact", "when should I clear context", "getting long", or proactively at phase boundaries and session transitions.

navigation main article SKILL.md
schedule Updated 2 months ago
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Browse Agent Skills by Occupation

23 major groups · 867 SOC occupations

Browse by Category

Explore agent skills organized by their primary use case

SKILLMD / CREATORS AND OCCUPATION CATEGORIES

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.

SEO KNOWLEDGE HUB & TECHNICAL OVERVIEW

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.

8 QUESTIONS

Frequently Asked Questions

A practical guide to agent skills: what they are, how to inspect them, and how SkillMD helps you explore the ecosystem.