LLM & Agents

LLM-only skill that accepts a repository structure dump, README, and notes, and returns a standardized markdown snapshot, condensed memory summary, and human checklist. No external HTTP requests or web search.

Database schema RAG system. Activates when working with database tables, migrations, queries, or schema changes.

Scrape external documentation (API references, library docs, protocol specifications) and generate Claude Agent Skills in SKILL.md format. Use when creating skills from documentation, integrating third-party knowledge, or building domain-specific skills. Parses HTML/Markdown, extracts structure, generates proper frontmatter and instructions. Triggers on "scrape documentation", "docs to skill", "generate skill from docs", "API documentation to skill".

Use when starting any conversation - establishes mandatory workflows for finding and using skills, including using Skill tool before announcing usage, following brainstorming before coding, and creating TodoWrite todos for checklists

Create hierarchical project plans optimized for solo agentic development. Use when planning projects, phases, or tasks that Claude will execute. Produces Claude-executable plans with verification criteria, not enterprise documentation. Handles briefs, roadmaps, phase plans, and context handoffs.

Creates new Claude Code skills following best practices. Guides through skill structure,naming, descriptions, and progressive disclosure. Use when user wants to create a skill,build a skill, make a new capability, or asks about skill best practices.

Generate beautiful infographic PNG images from Claude Code changelog summaries. Use this skill after changelog-interpreter has generated a user-friendly summary, to create a visual representation that can be saved and shared.

Searching internet for technical documentation using llms.txt standard, GitHub repositories via Repomix, and parallel exploration. Use when user needs: (1) Latest documentation for libraries/frameworks, (2) Documentation in llms.txt format, (3) GitHub repository analysis, (4) Documentation without direct llms.txt support, (5) Multiple documentation sources in parallel

Expert on Shelby Protocol decentralized blob storage on Aptos blockchain. Coordinates 7 specialized sub-skills covering protocol architecture, SDK usage, smart contracts, CLI tools, RPC infrastructure, dApp building, and storage integration. Triggers on keywords Shelby Protocol, Shelby storage, decentralized storage, Aptos storage, blob storage, Shelby.

Generate comprehensive app-spec.txt project specifications for autonomous software development. Use this skill when the user wants to create a detailed project specification, plan a new application, or set up an autonomous development workflow. This skill produces specifications compatible with the initializer-agent + coding-agent pattern.

Expert FDA regulatory consultant specializing in medical devices, pharmaceuticals, biologics, and combination products

Generates test cases, creates mocks, identifies edge cases, analyzes coverage gaps, and supports property-based, mutation, and contract testing. Use when writing tests, improving coverage, detecting flaky tests, or implementing advanced testing strategies.

Expert on Shelby Protocol smart contracts on Aptos blockchain. Helps with blob metadata, micropayment channels, auditing system, storage commitments, placement group assignments, Move modules, and on-chain state management. Triggers on keywords Shelby smart contract, Shelby Move, blob metadata, micropayment channel, Shelby auditing, placement group assignment, storage commitment, Aptos contract.

Starts a session and generates a startup prompt for use in the target project repo. Use when user wants to start a session, generate a startup prompt, or begin working on a project.

Write Vitest unit tests and browser mode component tests for TypeScript projects. Use when asked to write tests, create test files, add test coverage, fix failing tests, test React components with browser mode, or work with Vitest testing patterns. Handles both unit testing with Given-When-Then pattern and React component testing with vitest-browser-react.

Moving average based forecasting for smoothed predictions

Tests JavaScript and TypeScript applications with Vitest including unit tests, mocking, coverage, and React component testing. Use when writing tests, setting up test infrastructure, mocking dependencies, or measuring code coverage.

Designs database schemas, data models, and database architectures

Memory system with three MCP tools: mcp__plugin_kg_kodegen__memory_list_libraries (discover namespaces), mcp__plugin_kg_kodegen__memory_memorize (store with embeddings), mcp__plugin_kg_kodegen__memory_recall (semantic search). Use for storing/retrieving knowledge by meaning. WHEN: User says "remember this", "recall", "what did I save", "my notes", "find my knowledge about". WHEN NOT: File operations (use fs_*), exact keyword search (use fs_search).

Capture important decisions made during Claude Code sessions and store them in searchable, structured format for future reference. Automatically triggers on decision keywords or manual request.