Explore skills

Generative Engine Optimization — optimize content for AI search engines (ChatGPT, Perplexity, Google AI Overviews, Gemini). Use when user wants to rank in AI search, improve AI citability, audit content for LLM visibility, or explicitly invokes /geo commands. Triggers on "GEO", "generative engine", "AI search", "AI overviews", "citability", "Perplexity", "ChatGPT search", or /geo commands.

Manually-triggered comprehensive codebase health audit covering security, architecture, documentation drift, dead code, and test coverage gaps. Produces a ranked markdown report, files prioritized GitHub issues, and proposes (but never autonomously opens) auto-fix PRs for trivial safe changes. Use when the user wants to audit, scan, review the health of, do a security check on, find dead code in,

Capture the current state of a project by updating documentation at the end of a development session. Invokes the readme skill to refresh README.md and the planning-with-files skill to record project status in a doc/ or docs/ directory. Use after merging a PR, finishing a feature, wrapping up a coding session, or any time the user wants to snapshot where the project stands — even implicit phrases

Use when the user wants to prevent broken code from being pushed, block git push when tests fail, run tests before push, set up push protection, or add a safety net against pushing untested code. Covers any request to gate pushes on test results — whether they mention "hook", "pre-push", or just describe wanting to stop bad code from reaching the remote. Also handles auto-fix/auto-repair of test f

Comprehensive document creation, editing, and analysis with support for tracked changes, comments, formatting preservation, and text extraction. When Claude needs to work with professional documents (.docx files) for: (1) Creating new documents, (2) Modifying or editing content, (3) Working with tracked changes, (4) Adding comments, or any other document tasks

Audits a working feature for the gap between "happy path passes" and "production-ready" — edge cases, error handling, loading/empty/error states, a11y, responsive, i18n, observability, ops hooks. Use when a feature works but needs polish, for "완성도 높여줘", "production ready로", "edge case 검토", "polish this feature", "is this ready to ship?", "엣지 케이스 다 챙겼나", "PR 전 점검", "빠진 상태 없나", or before shipping an

SAP ABAP RESTful Application Programming Model (RAP) development skill. End-to-end scope: business objects (BO), CDS data model, behavior definitions and implementations, service definitions / bindings, file uploads/downloads, metadata extensions, value helps, and RAP testing. Use when the user asks to: build a RAP BO (managed or unmanaged), model CDS view entities / table entities / projection vi

Map the high-level microservice architecture and generate per-service spec .md files that give AI agents full context — owned APIs, DB tables, events, inter-service dependencies, and data flows. Use when user wants to document microservice interactions, generate context files for AI agents, understand service boundaries, or says "ms-spec" or "map my services".

Systematic pricing auditor that builds a solid, defensible price step by step — even with incomplete data. Use when the user needs help pricing a project, service, or offer and doesn't know where to start, is guessing, or wants to pressure-test their number. Trigger on: "what should I charge", "how do I price this", "is this price fair", "I don't know what to ask for", "help me price", or any situ

Generates a branch-vs-default comparison report with plain-language explanations and senior dev review. Use when the user asks to summarize, compare, review, or explain branch changes, or wants a PR summary before merging.

Use when working in this dotfiles repository - modifying shell configs, SSH, neovim, or scripts. Covers symlink architecture, agent selection, and permission model.

Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).