Use this file to find the right skill for your task. Read the skill's SKILL.md or README before using it.
Agents should trigger skills by task intent, not only when the user names a skill.
- Classify the work: debugging, README, research audit, security, frontend, browser, MCP, documents, game, writing, memory, or architecture.
- Search this index for matching
What/Whenlines. - Read the selected skill's
SKILL.md. - Follow the skill's workflow and use bundled scripts/references when relevant.
- If no existing skill fits a complex task, search curated resources or public upstreams before inventing a workflow.
Public-safety note: this index is documentation, not a credential store. Do not add API keys, tokens, private paths with secrets, or account state.
Core development workflows for systematic, high-quality work.
- What: Root cause investigation before proposing fixes; prevents symptom-based patching
- When: Any bug, test failure, unexpected behavior, or performance problem
- Path: D:\agent-resources\skills\obra-superpowers\systematic-debugging
- What: Write tests first, then implementation; ensures correctness and prevents regressions
- When: Implementing any feature or bugfix before writing implementation code
- Path: D:\agent-resources\skills\obra-superpowers\test-driven-development
- What: Coordinate multiple independent tasks across agents without shared state
- When: Facing 2+ independent tasks that can be worked on without sequential dependencies
- Path: D:\agent-resources\skills\obra-superpowers\dispatching-parallel-agents
- What: Evaluate and implement code review feedback with technical rigor
- When: Receiving code review feedback, especially if unclear or technically questionable
- Path: D:\agent-resources\skills\obra-superpowers\receiving-code-review
- What: Prepare work for peer review to verify requirements and quality
- When: Completing tasks, implementing major features, or before merging
- Path: D:\agent-resources\skills\obra-superpowers\requesting-code-review
- What: Create isolated workspaces for feature work using native git tools
- When: Starting feature work that needs isolation from current workspace
- Path: D:\agent-resources\skills\obra-superpowers\using-git-worktrees
- What: Run verification commands and confirm output before claiming success
- When: About to claim work is complete, fixed, or passing before committing/PRs
- Path: D:\agent-resources\skills\obra-superpowers\verification-before-completion
- What: Delegate work to specialized sub-agents with clear specs and verification
- When: Complex tasks requiring multiple specialized agents or parallel work
- Path: D:\agent-resources\skills\obra-superpowers\subagent-driven-development
- What: Create detailed execution plans before starting implementation
- When: Starting complex multi-step tasks or unfamiliar work
- Path: D:\agent-resources\skills\obra-superpowers\writing-plans
- What: Follow execution plans systematically with progress tracking
- When: Working through complex multi-step tasks
- Path: D:\agent-resources\skills\obra-superpowers\executing-plans
Anthropic-specific tools and integrations.
- What: Build, debug, and optimize Claude API / Anthropic SDK apps with prompt caching
- When: Code imports anthropic/@anthropic-ai/sdk; adding Claude features (caching, thinking, tool use, batch, files)
- Path: D:\agent-resources\skills\anthropics\claude-api
- What: Create high-quality MCP servers for LLM integration with external services
- When: Building MCP servers in Python (FastMCP) or Node/TypeScript (MCP SDK)
- Path: D:\agent-resources\skills\anthropics\mcp-builder
- What: Test local web applications using Playwright; verify UI, debug behavior, capture screenshots
- When: Testing frontend functionality or debugging UI behavior
- Path: D:\agent-resources\skills\anthropics\webapp-testing
- What: Create complex claude.ai HTML artifacts with React, Tailwind CSS, shadcn/ui
- When: Building elaborate multi-component artifacts requiring state management or routing
- Path: D:\agent-resources\skills\anthropics\web-artifacts-builder
- What: Create, modify, and optimize skills; run evals and benchmark performance
- When: Creating new skills, editing existing ones, or optimizing skill descriptions
- Path: D:\agent-resources\skills\anthropics\skill-creator
- What: Collaborate on document creation and editing
- When: Co-authoring documents with Claude
- Path: D:\agent-resources\skills\anthropics\doc-coauthoring
- What: Extract, analyze, and manipulate PDF documents
- When: Working with PDF files programmatically
- Path: D:\agent-resources\skills\anthropics\pdf
- What: Create and manipulate Word documents
- When: Generating or editing .docx files
- Path: D:\agent-resources\skills\anthropics\docx
- What: Create and manipulate Excel spreadsheets
- When: Generating or editing .xlsx files
- Path: D:\agent-resources\skills\anthropics\xlsx
- What: Create and manipulate PowerPoint presentations
- When: Generating or editing .pptx files
- Path: D:\agent-resources\skills\anthropics\pptx
- What: Design visual layouts and graphics
- When: Creating visual designs or layouts
- Path: D:\agent-resources\skills\anthropics\canvas-design
- What: Design and build frontend interfaces
- When: Creating frontend designs and implementations
- Path: D:\agent-resources\skills\anthropics\frontend-design
- What: Apply and maintain brand consistency
- When: Ensuring brand compliance in designs
- Path: D:\agent-resources\skills\anthropics\brand-guidelines
- What: Generate and manage design themes
- When: Creating or customizing design themes
- Path: D:\agent-resources\skills\anthropics\theme-factory
- What: Create animated GIFs for Slack
- When: Generating GIF content for Slack messages
- Path: D:\agent-resources\skills\anthropics\slack-gif-creator
- What: Generate algorithmic art and visualizations
- When: Creating generative art or algorithmic visualizations
- Path: D:\agent-resources\skills\anthropics\algorithmic-art
Official shadcn/ui skill + full source mirror. shadcn is a code-distribution platform: components are added as editable source into the project via the shadcn@latest CLI (not a runtime dependency). MIT licensed. Full upstream repo mirrored at D:\agent-resources\repos\shadcn-ui (apps, packages, templates, registry, evals).
- What: Add / search / compose / fix / theme shadcn/ui components and presets; injects live project context (
components.json, installed components, aliases, tailwind version) and enforces composition + styling rules (semantic tokens, Field/FieldGroup forms, data-icon, gap over space-y). - When: Any project with a
components.json; building or upgrading React/Next/Vite UIs; "shadcn init", "add ", "apply --preset", theming, or component debugging. Auto-triggers by task intent, not only when named. - Use: run all CLI via the project's package runner (
npx/pnpm dlx/bunx --bunshadcn@latest). Read SKILL.mdrules/*.md(styling, forms, composition, icons, base-vs-radix) before writing component markup. - Path: D:\agent-resources\skills\shadcn (→ repos\shadcn-ui\skills\shadcn)
- Repo: D:\agent-resources\repos\shadcn-ui
Systematic approaches to context, documentation, and development practices.
- What: Test-driven development methodology
- When: Implementing features with test-first approach
- Path: D:\agent-resources\skills\context-engineering-kit\tdd
- What: Domain-driven design principles
- When: Designing systems around business domains
- Path: D:\agent-resources\skills\context-engineering-kit\ddd
- What: Specification-driven development
- When: Implementing from detailed specifications
- Path: D:\agent-resources\skills\context-engineering-kit\sdd
- What: Specification-and-architecture-driven development
- When: Complex systems requiring both spec and architecture planning
- Path: D:\agent-resources\skills\context-engineering-kit\sadd
- What: Code review practices and workflows
- When: Reviewing code or preparing for review
- Path: D:\agent-resources\skills\context-engineering-kit\review
- What: Reflection and learning from past work
- When: Analyzing past decisions and outcomes
- Path: D:\agent-resources\skills\context-engineering-kit\reflexion
- What: Continuous improvement methodology
- When: Incrementally improving processes or code
- Path: D:\agent-resources\skills\context-engineering-kit\kaizen
- What: Git workflows and best practices
- When: Working with version control
- Path: D:\agent-resources\skills\context-engineering-kit\git
- What: Model Context Protocol practices
- When: Working with MCP servers and tools
- Path: D:\agent-resources\skills\context-engineering-kit\mcp
- What: Documentation best practices
- When: Writing or maintaining documentation
- Path: D:\agent-resources\skills\context-engineering-kit\docs
- What: Fail-fast, fail-forward principles
- When: Rapid iteration and learning
- Path: D:\agent-resources\skills\context-engineering-kit\fpf
- What: Technology stack selection and management
- When: Choosing or evaluating tech stacks
- Path: D:\agent-resources\skills\context-engineering-kit\tech-stack
- What: Customize agent behavior and capabilities
- When: Configuring agents for specific tasks
- Path: D:\agent-resources\skills\context-engineering-kit\customaize-agent
Specialized skills for workstation maintenance, Lark, communication, and content creation.
- What: Safely inventory, classify, organize, and maintain Vipin's Windows workstation across C:/, D:/, and G:/, including file-level approved moves, D-drive root move-with-junction organization, devtools, AGENT_RESOURCE/agent-resources, AGENTIC_SCIENCE/UUPF, WEIPING_WIKI, agent skill sync, preflight, broad-approval execution, and rollback
- When: Cleaning up drives, organizing local files or D-root directories, protecting D:/Research plus AGENT_RESOURCE, AGENTIC_SCIENCE, devtools, and public devtools exports, preparing type-grouped 30-day-age-gated batch-confirmed file moves, preflighting all batches without moving files, moving eligible D-root directories into D:/_Organized while preserving old paths as junctions, executing broadly approved low-risk batches, or coordinating agent infrastructure upgrades with weiping-wiki public-safe docs
- Path: D:\agent-resources\skills\vipin\workstation-maintenance
- What: Turn any project into an AI-readable, maintainable, verifiable causal layer under
<project>/.agent/(architecture, glossary, constraints, modules, flows, entities, causal-graph, decisions, tasks), and harden vague requirements into concrete task specs (goal, modules, edit paths, risks, acceptance criteria, test commands). Engine lives in WEIPING_WIKI (python scripts/wiki.py hardness); facts stay project-local, only cross-project lessons sync to agentmemory - When: Starting work on an unfamiliar/large project, needing a change's blast radius or do-not-modify boundaries, or hardening a vague requirement before editing. Applies to every agent
- Path: D:\agent-resources\skills\vipin\project-hardness
- What: Convert prose, novel, biography, history, or book-archive sources into manga adaptation packages with candidate scoring, source extraction, manga bibles, chapter/page/panel scripts, storyboard briefs, and image prompt packs
- When: Selecting works from
D:\Company\anime\literature-books, adapting local book files into comics or manga, ranking adaptation candidates, or generating character/scene/panel prompt packages from prose - Path: D:\agent-resources\skills\vipin\literature-to-manga
- What: Command-line interface for Lark platform operations
- When: Automating Lark operations via CLI
- Path: D:\agent-resources\skills\vipin\lark-cli
- What: Lark Base (database) operations and automation
- When: Working with Lark Base databases
- Path: D:\agent-resources\skills\vipin\lark-base
- What: Lark Doc (document) creation and management
- When: Creating or managing Lark documents
- Path: D:\agent-resources\skills\vipin\lark-doc
- What: Lark Sheets (spreadsheet) operations
- When: Working with Lark spreadsheets
- Path: D:\agent-resources\skills\vipin\lark-sheets
- What: Lark Drive (file storage) operations
- When: Managing files in Lark Drive
- Path: D:\agent-resources\skills\vipin\lark-drive
- What: Lark Calendar operations and scheduling
- When: Managing calendar events in Lark
- Path: D:\agent-resources\skills\vipin\lark-calendar
- What: Lark Contact management
- When: Managing contacts in Lark
- Path: D:\agent-resources\skills\vipin\lark-contact
- What: Lark Instant Messaging operations
- When: Sending messages via Lark
- Path: D:\agent-resources\skills\vipin\lark-im
- What: Lark Wiki (knowledge base) operations
- When: Creating or managing Lark Wiki content
- Path: D:\agent-resources\skills\vipin\lark-wiki
- What: Lark Slides (presentation) creation
- When: Creating presentations in Lark
- Path: D:\agent-resources\skills\vipin\lark-slides
- What: Lark Markdown formatting and conversion
- When: Working with Markdown in Lark
- Path: D:\agent-resources\skills\vipin\lark-markdown
- What: Explore and test Lark OpenAPI
- When: Testing Lark API endpoints
- Path: D:\agent-resources\skills\vipin\lark-openapi-explorer
- What: Shared Lark utilities and helpers
- When: Using common Lark functionality
- Path: D:\agent-resources\skills\vipin\lark-shared
- What: Create custom Lark skills
- When: Building new Lark integrations
- Path: D:\agent-resources\skills\vipin\lark-skill-maker
- What: Bridge between Feishu and other systems
- When: Integrating Feishu with external services
- Path: D:\agent-resources\skills\vipin\feishu-bridge
- What: Assist with communication tasks
- When: Drafting or managing communications
- Path: D:\agent-resources\skills\vipin\communication-assistant
- What: Email management and automation
- When: Handling email tasks
- Path: D:\agent-resources\skills\vipin\email-assistant
- What: Create and publish content
- When: Publishing content to multiple platforms
- Path: D:\agent-resources\skills\vipin\content-creation-publisher
- What: Automate Chrome browser tasks
- When: Automating browser interactions
- Path: D:\agent-resources\skills\vipin\chrome-automation
- What: Frontend design and implementation
- When: Creating frontend designs
- Path: D:\agent-resources\skills\vipin\frontend-design
- What: Generate README files from templates
- When: Creating project documentation
- Path: D:\agent-resources\skills\vipin\readme-blueprint-generator
- What: Publish videos to WeChat channels
- When: Publishing video content to WeChat
- Path: D:\agent-resources\skills\vipin\wechat-video-channel-publish
- What: Orchestrate academic paper workflows
- When: Managing academic paper projects
- Path: D:\agent-resources\skills\vipin\paper-orchestra
Security and testing expertise.
- What: Audit agent actions for security and correctness
- When: Reviewing agent behavior and decisions
- Path: D:\agent-resources\skills\trailofbits\agentic-actions-auditor
- What: Identify and clarify underspecified requirements
- When: Requirements are vague or incomplete
- Path: D:\agent-resources\skills\trailofbits\ask-questions-if-underspecified
- What: Audit how context is built and used
- When: Reviewing context management
- Path: D:\agent-resources\skills\trailofbits\audit-context-building
- What: Design and implement secure smart contracts
- When: Building blockchain contracts
- Path: D:\agent-resources\skills\trailofbits\building-secure-contracts
- What: Perform static code analysis
- When: Analyzing code for issues without execution
- Path: D:\agent-resources\skills\trailofbits\static-analysis
- What: Test code quality via mutation testing
- When: Evaluating test suite effectiveness
- Path: D:\agent-resources\skills\trailofbits\mutation-testing
- What: Generate test cases via property-based testing
- When: Testing with generated inputs
- Path: D:\agent-resources\skills\trailofbits\property-based-testing
- What: Create Semgrep rules for code analysis
- When: Building custom static analysis rules
- Path: D:\agent-resources\skills\trailofbits\semgrep-rule-creator
- What: Analyze code variants for consistency
- When: Comparing similar code implementations
- Path: D:\agent-resources\skills\trailofbits\variant-analysis
- What: Audit supply chain security risks
- When: Evaluating dependency and integration risks
- Path: D:\agent-resources\skills\trailofbits\supply-chain-risk-auditor
- What: Analyze code for timing vulnerabilities
- When: Reviewing cryptographic or security-sensitive code
- Path: D:\agent-resources\skills\trailofbits\constant-time-analysis
- What: Review code changes systematically
- When: Reviewing pull requests or diffs
- Path: D:\agent-resources\skills\trailofbits\differential-review
- What: Verify code matches specifications
- When: Ensuring implementation matches spec
- Path: D:\agent-resources\skills\trailofbits\spec-to-code-compliance
Specialized single-purpose skills.
- What: GSAP animation library core concepts
- When: Working with GSAP animations
- Path: D:\agent-resources\skills\standalone\gsap-core
- What: GSAP integration with React
- When: Using GSAP in React projects
- Path: D:\agent-resources\skills\standalone\gsap-react
- What: GSAP ScrollTrigger plugin for scroll animations
- When: Creating scroll-based animations
- Path: D:\agent-resources\skills\standalone\gsap-scrolltrigger
- What: GSAP Timeline for complex animations
- When: Orchestrating multiple animations
- Path: D:\agent-resources\skills\standalone\gsap-timeline
- What: GSAP plugin ecosystem
- When: Using advanced GSAP plugins
- Path: D:\agent-resources\skills\standalone\gsap-plugins
- What: Optimize GSAP animation performance
- When: Improving animation performance
- Path: D:\agent-resources\skills\standalone\gsap-performance
- What: GSAP integration with frameworks
- When: Using GSAP with Vue, Angular, etc.
- Path: D:\agent-resources\skills\standalone\gsap-frameworks
- What: GSAP utility functions and helpers
- When: Using GSAP utilities
- Path: D:\agent-resources\skills\standalone\gsap-utils
- What: Darwin evolutionary algorithm implementation
- When: Implementing genetic algorithms
- Path: D:\agent-resources\skills\standalone\darwin-skill
- What: MIT-licensed person/mentor skill distillation workflow ("女娲造人"): deep research -> thinking-frame extraction -> runnable perspective skill.
- When: The user wants to create, update, or choose a person/topic perspective skill from an explicit name or a vague thinking/decision need.
- Path: D:\agent-resources\skills\standalone\nuwa-skill
- What: HTML-native design skill (花叔Design) — high-fidelity prototypes, interactive Demos, slide decks, motion/animation, design-variation exploration, plus a design-direction advisor and expert design review; embodies the matching expert (UX / animator / slide designer / prototyper).
- When: User asks for UI/UX, prototype/mockup, slide deck/presentation, motion graphics/animation, infographic, or "explore a few design directions"; any visual or design-fidelity work in HTML.
- Path: D:\agent-resources\skills\standalone\huashu-design
- What: Colleague agent collaboration
- When: Working with colleague agents
- Path: D:\agent-resources\skills\standalone\colleague-skill
- What: Anbeime platform integration
- When: Working with Anbeime
- Path: D:\agent-resources\skills\standalone\anbeime-skill
- What: DeepSeek MCP server integration
- When: Using DeepSeek models via MCP
- Path: D:\agent-resources\skills\standalone\deepseek-mcp
- What: Matt Pocock's TypeScript and web development skills
- When: Advanced TypeScript or web development patterns
- Path: D:\agent-resources\skills\standalone\mattpocock-skills
- What: AI video generation for piano performances
- When: Creating AI-generated piano videos
- Path: D:\agent-resources\skills\standalone\canon-pianist-ai-video-project
Composio automation integrations (1000+ services).
Composio provides automation skills for integrating with external services. Key categories include:
- Communication: Slack, Discord, Telegram, WhatsApp, Email services
- Project Management: Jira, Asana, Monday.com, Trello, Linear
- CRM: Salesforce, HubSpot, Pipedrive, Zoho
- Finance: Stripe, PayPal, QuickBooks, Xero
- Cloud: AWS, Google Cloud, Azure, DigitalOcean
- Data: Airtable, Notion, Google Sheets, Zapier
- AI/ML: OpenAI, Anthropic, Hugging Face, Replicate
- Web: Shopify, WordPress, Webflow, Wix
- Analytics: Google Analytics, Mixpanel, Amplitude
- And 900+ more services
Path: D:\agent-resources\skills\composio{service-name}-automation
Graph visualization and analysis.
- What: Create and analyze graph visualizations
- When: Visualizing network or hierarchical data
- Path: D:\agent-resources\skills\graphify\graphify
These are always-available MCP servers, not file-based skills. Any agent sharing the CC MCP config can use them directly.
- What: Generate images via gpt-image-2 (OpenAI), saves to local disk
- When: Need to create illustrations, diagrams, banners, paper figures, any image generation task
- How: MCP tool call (auto-available in CC/ARIS sessions), uses 9100 rotator
- What: Persistent shared memory — search, recall, lessons, signals, actions
- When: Always (session start search, cross-agent communication, saving lessons)
- How: MCP tool calls (memory_smart_search, memory_recall, memory_save, etc.)
- What: Invoke Codex/GPT-5.5 as an external reviewer
- When: Research review, code audit, getting a second opinion from a different model
- How: MCP tool call, used by ARIS /research-review and /auto-review-loop skills
232 skills + 60 agents for Claude Code, Codex, Cursor, OpenCode, Gemini, and more. The most comprehensive open-source agent harness available.
Install (plugin, recommended):
/plugin marketplace add https://github.com/affaan-m/ECC
/plugin install ecc@ecc
Key commands: /ecc:plan, /code-review, /security-scan, /build-fix, /refactor-clean, /test-coverage, /instinct-status, /evolve, /harness-audit
Components at D:\agent-resources\skills\ecc\:
skills/— 232 workflow skills (TDD, security, frontend, backend, ML, agent-harness, etc.)agents/— 60 specialized subagents (architect, code-reviewer, security-reviewer, tdd-guide, planner, etc.)rules/— always-on coding guidelines (common + language-specific: TS, Python, Go, Swift, PHP)hooks/— event-driven automations (tool use, session start/stop, file edits)mcp-configs/— MCP server definitions (GitHub, Supabase, Vercel, etc.)COMMANDS-QUICK-REF.md— full command referencethe-shortform-guide.md— quick-start guide
Notable features:
- AgentShield: 102-rule security scanner for CLAUDE.md, hooks, MCP configs
- Continuous Learning v2: instinct extraction with confidence scoring
- Dashboard GUI:
python3 ecc_dashboard.pyornpm run dashboard - Hook tuning via env vars:
ECC_HOOK_PROFILE=minimal|standard|strict
Path: D:\agent-resources\skills\ecc\
Four-piece deployment (四件套, 2026-06-08): ECC is wired into the agent family across four pillars — see D:\devtools\AGENTS.md for the per-agent matrix.
- Skills: each agent's
skills\eccis now a junction toD:\agent-resources\skills\ecc(CC + Codex converted from drifted copies; old copies archived*.prejxn). Do NOT run ECC'sinstall-apply.jsagainst a live home — it doescopyFileSyncand re-creates drift; junction by hand instead. - Intuition:
D:\devtools\agent-hooks\ecc-observe.cmd(nodeobserve-runner.js, NOTobserve.sh) wired additively into CCsettings.json; default OFF via marker, toggleecc-intuition-toggle.cmd.CLV2_HOMUNCULUS_DIR=/d/devtools/data/derived/clv2-homunculus,CLAUDE_PLUGIN_ROOT=D:\agent-resources\repos\ECC(full repo, hasscripts/). - Memory: ECC homunculus is a derivation layer only →
data\derived\lessons\pending\ecc\→ promoted byscripts\ingest-lessons.mjs. agentmemory stays the single source. - Security: pinned
ecc-agentshield@1.4.0atD:\devtools\agent-tools\agentshield\, run viabin\agentshield-scan.cmd(baseline-delta, nightly), never inlined into hooks.
NousResearch self-improving agent — ambient/background role (gateway, cron, lesson curation). Full independent Python agent, NOT a skill pack.
- Source:
D:\devtools\vendor\hermes-agent; venv + home:D:\devtools\hermes(Python 3.11); launcher:D:\devtools\hermes.cmd(pinsHERMES_HOMEto D-drive). - Model: gpt-5.5 relay (中转) via
hermes\config.yaml. agentmemory MCP wired; native memory/session_search demoted. agentskills.io-compatible. - See
D:\devtools\AGENTS.mdfor full wiring.
Behavioral guidelines derived from Andrej Karpathy's observations on LLM coding pitfalls.
- What: Four coding principles — Think Before Coding, Simplicity First, Surgical Changes, Goal-Driven Execution
- When: Writing, reviewing, or refactoring any code to avoid overcomplication and scope creep
- Path: D:\agent-resources\skills\standalone\karpathy-guidelines
Turn any codebase or knowledge base into an interactive knowledge graph.
- What: Build a knowledge graph from a codebase using Tree-sitter + LLM semantic analysis
- When: Starting work on an unfamiliar codebase; need architecture overview
- Path: D:\agent-resources\skills\standalone\understand
- What: Ask natural language questions about the codebase knowledge graph
- When: Exploring how components relate, tracing data flows, answering "where is X"
- Path: D:\agent-resources\skills\standalone\understand-chat
- What: Open the interactive visual knowledge graph explorer
- When: Need a visual map of the codebase structure
- Path: D:\agent-resources\skills\standalone\understand-dashboard
- What: Analyze the impact of current changes on the codebase graph
- When: Before committing; want to know what a change touches
- Path: D:\agent-resources\skills\standalone\understand-diff
- What: Deep-dive explanation of a specific file or function
- When: Need to understand a complex module in detail
- Path: D:\agent-resources\skills\standalone\understand-explain
- What: Generate an onboarding guide for new team members
- When: Onboarding someone to a codebase; writing contributor docs
- Path: D:\agent-resources\skills\standalone\understand-onboard
- What: Extract business domain knowledge (domains, flows, steps) from code
- When: Need to understand business logic embedded in the codebase
- Path: D:\agent-resources\skills\standalone\understand-domain
- What: Analyze a Karpathy-pattern LLM wiki into a knowledge graph
- When: Working with a wiki-style knowledge base (markdown files)
- Path: D:\agent-resources\skills\standalone\understand-knowledge
Create high-impact, interactive HTML presentations through AI collaboration.
- What: Build standalone HTML slide decks with shared design system, data viz, offline-first
- When: Creating training materials, pitch decks, tech talks, or any visual storytelling
- Path: D:\agent-resources\skills\standalone\presentation-as-code
Pre-indexed code knowledge graph for AI agents — fewer tokens, fewer tool calls, 100% local.
- What: Add a new language to CodeGraph's tree-sitter parser
- When: Working with a language not yet supported by CodeGraph
- Path: D:\agent-resources\skills\standalone\codegraph-add-lang
- What: Evaluate agent performance against CodeGraph benchmarks
- When: Benchmarking or comparing agent behavior on codebase queries
- Path: D:\agent-resources\skills\standalone\codegraph-agent-eval
Official Anthropic-managed plugins for Claude Code workflows.
- What: Automated PR code review using multiple specialized agents with confidence scoring
- When: Reviewing pull requests; want multi-agent review with structured output
- Path: D:\agent-resources\skills\claude-plugins-official\code-review
- What: End-to-end feature development workflow with agents and commands
- When: Implementing a new feature from spec to code
- Path: D:\agent-resources\skills\claude-plugins-official\feature-dev
- What: Modernize legacy code to current language/framework standards
- When: Upgrading old codebases, migrating deprecated APIs
- Path: D:\agent-resources\skills\claude-plugins-official\code-modernization
- What: Comprehensive PR review toolkit with agents and commands
- When: Thorough pull request review with structured checklist
- Path: D:\agent-resources\skills\claude-plugins-official\pr-review-toolkit
- What: Build agents using the Claude Agent SDK
- When: Creating custom agents with the Anthropic Agent SDK
- Path: D:\agent-resources\skills\claude-plugins-official\agent-sdk-dev
- What: Security review and guidance for code changes
- When: Security-sensitive code; want automated security analysis
- Path: D:\agent-resources\skills\claude-plugins-official\security-guidance
- What: Simplify and reduce complexity in existing code
- When: Code is too complex, over-engineered, or hard to read
- Path: D:\agent-resources\skills\claude-plugins-official\code-simplifier
- What: Structured git commit workflow with conventional commits
- When: Creating commits with consistent format and quality
- Path: D:\agent-resources\skills\claude-plugins-official\commit-commands
- What: Set up Claude Code for a new project (CLAUDE.md, settings, hooks)
- When: Initializing Claude Code in a new repo
- Path: D:\agent-resources\skills\claude-plugins-official\claude-code-setup
- What: Manage and maintain CLAUDE.md files across a project
- When: Keeping CLAUDE.md up to date as the project evolves
- Path: D:\agent-resources\skills\claude-plugins-official\claude-md-management
- What: Set up MCP tunnels for remote/cloud MCP server access
- When: Connecting to MCP servers over network tunnels
- Path: D:\agent-resources\skills\claude-plugins-official\mcp-tunnels
- What: Create and manage Claude Code hooks with writing-rules skill
- When: Setting up automated hooks for Claude Code events
- Path: D:\agent-resources\skills\claude-plugins-official\hookify
- What: Generate structured session reports summarizing work done
- When: End of a work session; want a summary of changes and decisions
- Path: D:\agent-resources\skills\claude-plugins-official\session-report
- What: Build a production-ready MCP server from scratch
- When: Creating a new MCP server (more detailed than mcp-builder)
- Path: D:\agent-resources\skills\standalone\build-mcp-server
- What: Build an application that consumes MCP servers
- When: Creating a client app that uses MCP tools
- Path: D:\agent-resources\skills\standalone\build-mcp-app
- What: Generate a structured end-of-session report
- When: Wrapping up a work session; want a summary for handoff
- Path: D:\agent-resources\skills\standalone\session-report
- What: Rules for writing effective Claude Code hooks
- When: Creating hooks; want best practices for hook scripts
- Path: D:\agent-resources\skills\standalone\hookify-writing-rules
Comprehensive Claude Code skill suite for the full academic research pipeline — from ideation to publication.
- What: Socratic dialogue to walk through paper structure and research plan
- When: Starting a new paper; need to clarify research question, method, and contribution
- Path: D:\agent-resources\repos\academic-research-skills\academic-pipeline
- What: Human-in-the-loop writing assistance with style calibration and quality checks
- When: Drafting or revising paper sections; want AI to match your voice, not replace it
- Path: D:\agent-resources\repos\academic-research-skills\academic-paper
- What: Automated paper review with integrity gates (hallucination, citation, logic checks)
- When: Pre-submission review; want a structured checklist before submitting
- Path: D:\agent-resources\repos\academic-research-skills\academic-paper-reviewer
- What: Deep literature search and synthesis with trust-chain citation provenance
- When: Literature review; need to find, verify, and synthesize related work
- Path: D:\agent-resources\repos\academic-research-skills\deep-research
435-lesson, 20-phase open curriculum for building AI systems end-to-end (Python, TypeScript, Rust, Julia). Every lesson ships a reusable artifact.
- What: Structured curriculum from ML fundamentals to production agents and MCP servers
- When: Learning AI engineering systematically; building reference implementations
- Path: D:\agent-resources\repos\ai-engineering-from-scratch\phases
- What: Hands-on project templates for each curriculum phase
- When: Need a starter project for a specific AI engineering topic
- Path: D:\agent-resources\repos\ai-engineering-from-scratch\projects
Open-source personal AI super-intelligence harness — local memory, managed services, human-in-the-loop design.
- What: Personal AI assistant with local memory, tool integrations, and human-centered UX
- When: Building or extending a personal AI assistant; need a reference harness architecture
- Path: D:\agent-resources\repos\openhuman
Complete game development pipeline — from brainstorming to release.
- What: Full game studio hierarchy — directors, leads, specialists for Godot/Unity/UE5
- When: Building any game; need structured workflow (brainstorm → design → architecture → sprint → QA → release)
- Key skills: /start, /brainstorm, /create-architecture, /sprint-plan, /prototype, /vertical-slice, /playtest-report, /release-checklist
- Path: D:\agent-resources\skills\game-studios\
- Public status: local-only pending provenance/license clearance; do not route implicitly from the public index until cleared.
- What: Autonomous game generation pipeline with screenshot-based self-repair
- When: Want AI to generate a complete game from a description (Godot 4 / Bevy / Babylon.js)
- Key feature: Frame-grounded self-repair — judges progress from screenshots, not just compilation
- Path: D:\agent-resources\skills\godogen\
- Public status: local-only pending provenance/license clearance; do not route implicitly from the public index until cleared.
- What: Meta-prompting system that prevents context rot; breaks work into atomic plans
- When: Any complex project where "just prompting" produces bad results; need spec → plan → task → implement flow
- Note: Full runtime (not just skills) — reference for methodology. Use its workflow pattern.
- Path: D:\agent-resources\repos\gsd-2\
Autonomous novel writing AI agent with multi-agent pipeline and web workbench.
- What: Autonomous fiction writing — multi-agent pipeline (Radar→Planner→Composer→Architect→Writer→Observer→Reflector→Normalizer→Auditor→Reviser), 33-dimension auditing, style imitation, fan fiction, AIGC detection, EPUB export, InkOS Studio web UI
- When: Creative fiction writing, novel generation, short fiction packages, cover generation, chapter continuation/import, style analysis
- Path: D:\agent-resources\skills\inkos
215+ 个即插即用的中文 AI 专家角色(工程/设计/营销/产品/游戏/安全/金融等 18 部门)。 作为 Claude Code 子代理安装,不是 skill。详见 AGENCY-AGENTS.md。
- What: 211 个领域专家子代理(前端/后端/安全/DBA/SRE/UI/UX/小红书/抖音/跨境电商/政务/医疗合规/Qt 上位机 等),每个带独立人设、流程、交付物
- When: 需要某个具体领域的专家视角时;用
/<slug>调用(如/engineering-security-engineer)或让主 agent 自动路由 - 分层: T0 源仓库 / T0.5 slug 化无 BOM 暂存 / T1 ~30 精选常驻全局 / T2 按需灌入项目
- 安装:
install-agency(精选常驻)·install-agency -Category <x>·install-agency -All -Project .(按需) - 关键: 子代理 name 必须英文 slug,源仓库是中文 name,勿直接复制原始文件,必经暂存 slug 化
- 源: D:\agent-resources\repos\agency-agents-zh · 暂存: D:\agent-resources\staging\agency-claude
- 脚本: D:\devtools\agency-build-staging.ps1 · install-agency.ps1 · agency-fix-integration-bom.ps1
For comprehensive harness: ECC (232 skills + 60 agents at skills/ecc/)
For game development: GSD-2 (spec-driven). The local game-studios and godogen packs are useful for inspection but are not public-routed until provenance/license clearance is complete.
For debugging: systematic-debugging
For features: test-driven-development or feature-dev (plugin)
For parallel work: dispatching-parallel-agents
For code review: requesting-code-review, receiving-code-review, or code-review (plugin)
For Claude API: claude-api
For MCP servers: mcp-builder, build-mcp-server, or build-mcp-app
For testing web apps: webapp-testing
For complex artifacts: web-artifacts-builder
For Lark integration: lark-* skills
For security review: Trail of Bits skills or security-guidance (plugin)
For external services: Composio skills
For presentations: presentation-as-code
For codebase understanding: understand-* skills or codegraph
For coding discipline: karpathy-guidelines
For session wrap-up: session-report
For hooks: hookify or hookify-writing-rules
For academic research: academic-research-skills
For AI engineering curriculum: ai-engineering-from-scratch
For personal AI assistant: openhuman
For a domain-expert persona (211 roles): agency-agents — /<slug> e.g. /engineering-security-engineer; install via install-agency