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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danielfoerster-ccc

ccc-discovery-roleplay

by danielfoerster-ccc
star 0

Text-based Gap-Selling discovery call roleplay. Claude plays the prospect (grounded in their person file + behavioural signals + 1-2 active Kanter change-resistance threats), Daniel plays himself. Surfaces real objections, tests Daniel's discovery framing under pressure, scores his performance against the 4-step Gap Selling discovery (Facts/Problems/Impact/Root Cause + Future State + Intrinsic Motivation), and runs the CRM Challenge against the imagined notes. Ends with a debrief on what landed, what to sharpen, and what the prospect would actually think. USE THIS SKILL when Daniel says "roleplay [Name]", "simulate call with X", "practice call", "let's roleplay", "play [Name] for me", or when ccc-sales-prep has just run and Daniel wants to rehearse before the real call.

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schedule Updated 1 month ago
danielfoerster-ccc

ccc-pricing

by danielfoerster-ccc
star 0

Runs a structured pricing analysis for any CCC engagement. Loads client context, applies four converging pricing lenses — value-based (Weiss, Enns), Hormozi value equation, CCC offer architecture, and BenAI market reality (2 years AI automation pricing data) — then runs sanity checks and outputs a recommendation with full reasoning. Maintains a pricing log for compounding learning. USE THIS SKILL whenever Daniel needs to price an engagement, quote a client, decide between pricing options, or gut-check a number. Triggers on: 'what should I charge', 'price this', 'help me with pricing', 'what's the right price', 'am I overpricing', 'am I underpricing', 'quote for [client]', 'pricing for [client]', 'how much for this engagement'. Also trigger proactively when ccc-proposal-draft is building an offer and no price has been set.

navigation main article SKILL.md
schedule Updated 2 months ago
danielfoerster-ccc

gtm-discovery

by danielfoerster-ccc
star 0

Runs a structured GTM discovery process for AI automation businesses, producing ICP.md, positioning.md, voice.md, offer.md, and context.md. Use this skill whenever a founder, consultant, or AI automation professional needs to define or sharpen their market strategy — including niche selection, positioning, entry offer design, brand voice, and operational context (network, infrastructure, team, parallel objectives). Trigger on: "run the GTM process", "help me find my niche", "define my ICP", "what should I sell and to whom", "build my GTM foundation", "work through my positioning". Also trigger when a user wants to start or structure an AI automation consulting business.

navigation main article SKILL.md
schedule Updated 2 months ago
danielfoerster-ccc

ccc-wordpress-seo-implementation

by danielfoerster-ccc
star 0

Implements SEO fixes on WordPress client websites for CCC. Takes audit findings (from ccc-seo-audit, Seomator, or any SEO report) and systematically applies On-Page and technical improvements. Uses Chrome MCP for live site inspection and WPCode plugin for bulk Yoast meta operations — including the WPCode 3-Step Pattern for safe bulk meta-description and title updates. Covers the full implementation checklist: robots.txt, security headers (.htaccess), H1 tags, meta descriptions, page titles, OG image, canonical verification, and Yoast archive/sitemap settings. USE THIS SKILL when implementing SEO audit results on a WordPress site, setting meta descriptions or titles in bulk, fixing H1 tags across multiple pages, configuring Yoast settings, running a WordPress SEO implementation sprint for a CCC client, or any task that involves executing on SEO findings rather than just discovering them. Always use after ccc-seo-audit has been run.

navigation main article SKILL.md
schedule Updated 3 months ago
danielfoerster-ccc

ccc-seo-pillar-wave-launch

by danielfoerster-ccc
star 0

Designs the publishing sequence for one pillar's worth of articles — the wave. Takes a pillar from the topic-queue and produces an ordered, pinned week-by-week launch plan that modifies strict BFS-order with conversion-intent and volume-awareness: the strongest conversion-intent sub-silo ships first, then volume-champion sub-silos, then silo-hub and pillar-hub once cluster-content exists to link. Pins queue_position into the topic-files. Use this skill when an operator says "plan the wave for [Pillar]", "what order do I publish [Pillar] in", "sequence the first weeks", "launch plan for the pillar", "which article first", or after `ccc-seo-strategy-session` completes and the operator needs the first pillar's week-by-week order before `ccc-seo-publish-next`. Especially needed when the topic-queue is large and raw BFS-order would bury high-conversion articles behind low-value pillar-index pages.

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schedule Updated 15 days ago
danielfoerster-ccc

75-day-retro

by danielfoerster-ccc
star 0

Runs the 75-Day Retro — Todd Herman's load-bearing planning-through mechanism. Drafts the NEXT 90-day Roadmap through Step 9 (stopping before the first 2-Week Sprint definition) while still inside the current cycle. Triggers on Day 75 ± 5 of an active sprint. Eliminates end-of-cycle drift in days 76–90 — Day 91 becomes a slide, not a cold start. Reads the active sprint doc, 2-week-sprint-reviews, daily-checkout Scorecard data, and pillars-trend. Runs Herman's retro questions, re-scores the 5 Pillars vs. cycle baseline, builds a carry/retire/emerge Rock decision table, applies OPP + Good/Better/Best + Effort×Impact to next-sprint Rocks, proposes a next-cycle Theme (not locked), and harvests cycle-level rules to Decisions & Rules. THE MOST INVIOLABLE RITUAL — skip it and Day 91 cold-starts. USE on "75 day retro", "draft next sprint", "day 75 review", "plan-through retro", "next cycle draft", or when the active sprint is at Day 70-80.

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schedule Updated 15 days ago
danielfoerster-ccc

ccc-cashflow-quarterly-review

by danielfoerster-ccc
star 0

Runs the quarterly Profit First review cycle — gathers financial data, calculates CAPs (Current Allocation Percentages), compares progress to TAPs, distributes 50% of profit account as owner reward, adjusts allocation percentages for next quarter, and identifies focus areas. Triggers quarterly reviews, profit distribution execution, or CAP comparison tasks. Use when founder needs to complete their 90-day checkpoint, review progress toward allocation targets, celebrate profit distributions, or plan next quarter's profit points focus. Also: 4R review, Revisit Review Reap Reach, CBS score check, profit distribution, quarterly checkpoint, CDT update, allocation review.

navigation main article SKILL.md
schedule Updated 2 months ago
danielfoerster-ccc

ccc-audit-proposal

by danielfoerster-ccc
star 0

Generates the Phase 5b tiered commercial proposal from audit findings. Produces a 3-tier proposal (Quick Wins / Foundation / Full Transformation) with ROI calculations using the client's actual numbers. Works within the full audit flow (after the report) or standalone when fed discovery data from any client engagement. Pricing is set per engagement based on scope — not hardcoded. USE THIS SKILL when the audit report is done and it's time for pricing, when the user says 'write the proposal for [client]', 'create the pricing tiers', 'build the commercial proposal', 'generate the investment options', or 'put together the offer for [client]'. Also trigger when the consultant says 'they asked for a number' or 'I need to quote this'.

navigation main article SKILL.md
schedule Updated 2 months ago
danielfoerster-ccc

gtm-90-day-launch-plan

by danielfoerster-ccc
star 0

Produces a structured, actionable 90-day launch plan for AI automation businesses and consultants. Reads existing GTM foundation documents (ICP, positioning, voice, offer) when available, interviews the user about their current state, goals, capacity, and channels, then generates a phased plan with specific weekly actions, time budget, and a 90-day hypothesis. Use this skill when a user wants to: create a launch plan, quarterly execution roadmap, or go-to-market action plan. Also trigger on: "what should I do first", "how do I get my first client", "build me a plan for the next 90 days", "I need a launch roadmap", "help me plan my GTM execution", "plan out my next quarter". Works best after the GTM Discovery skill has run (foundation docs exist), but can operate without them by interviewing the user directly.

navigation main article SKILL.md
schedule Updated 15 days ago
danielfoerster-ccc

90-day-sprint-review

by danielfoerster-ccc
star 0

Runs a 90-day sprint closeout session. Loads the active sprint, scores Rocks against Good/Better/Best targets, runs a 5-question pattern debrief, Stop/Continue/Start, decision harvest, and 5 Pillars baseline→close delta. Appends harvested rules to Decisions & Rules, closes the sprint file with a footer, and outputs a dated Sprint Closeout note. Handles clean 90-day completions and mid-sprint strategic interrupts. Bridges to active Transition Sprint if running. Phase 0 guard: if today is Day 70-80 of an active sprint, suggests running 75-day-retro FIRST — the retro is the planning-through; this closeout is the closing. USE when operator says "sprint review", "90-day review", "close the sprint", "sprint closeout", "quarterly review", "end of sprint", "score my OKRs", "review the quarter", or after a major strategic pivot that supersedes the active sprint mid-course.

navigation main article SKILL.md
schedule Updated 15 days ago
danielfoerster-ccc

90-day-sprint

by danielfoerster-ccc
star 0

Runs a 90-Day Goal Attainment Sprint kickoff integrating Todd Herman's Achievement Phase mechanics onto Daniel's Boulder → Rock → Pebble → Activity hierarchy. Reads the active sprint and prior 75-day-retro draft to skip redundant questions, then runs Quarter Review → Vision → Theme → 5 Pillars baseline → Rocks (OPP "so that" framing + Good/Better/Best + Effort×Impact) → Pebbles → Activities. Produces THREE artifacts: the full Sprint doc, a condensed MAPIT action sheet, and a per-venture Entrepreneur Scorecard configuration that daily-checkout reads each evening. Use at quarter start, when resetting priorities, or to promote a 75-day-retro draft into a live sprint. Trigger on: "90-day plan", "quarterly planning", "new sprint", "reset OKRs", "plan next 90 days", "sprint kickoff", "promote retro draft", "Achievement Phase", "Pillars baseline", "MAPIT sheet".

navigation main article SKILL.md
schedule Updated 15 days ago
danielfoerster-ccc

scifi-excavation

by danielfoerster-ccc
star 0

Excavates visionary and science-fiction works for the *shape of workable futures* — mines a fictional world for its design specification (its telos) and connects that telos to the operator's real goals and projects. Not distillation, not archiving: the deliverable is a per-work excavation note (Facet / Adversary-as-stress-test / Earth-mirror / Telos extracted / Operator connection), never a plot summary. Runs a four-phase arc — Map, Excavate, Connect, Synthesise — across three epistemic layers (author-intent, the operator's own reading, the secondary critical body) with a path-dependency guard: never read the consensus before excavating your own reading. USE THIS SKILL whenever the user wants to ingest, mine, or excavate a science-fiction novel or series, says an SF book inspires a real project they want to build, mentions the Culture, Iain M. Banks, or Vernor Vinge, or asks to turn fiction into a design blueprint rather than summarize it. Phase-0 Tavily gate on all web reads.

navigation main article SKILL.md
schedule Updated 1 month 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.