graphify 是做什麼的？
用於回答任何關於程式碼庫、架構、檔案關係或專案內容的問題——尤其當 graphify-out/ 目錄存在時，應優先將其視為 graphify 查詢。能將任何輸入（程式碼、文件、論文、圖片、影片）轉換為帶有神節點、社群偵測以及查詢/路徑/解釋工具的持久化知識圖譜。
用於回答任何關於程式碼庫、架構、檔案關係或專案內容的問題——尤其當 graphify-out/ 目錄存在時，應優先將其視為 graphify 查詢。能將任何輸入（程式碼、文件、論文、圖片、影片）轉換為帶有神節點、社群偵測以及查詢/路徑/解釋工具的持久化知識圖譜。
graphify 是一個強大的 AI 代理技能，旨在將任何類型的輸入（包括程式碼、文件、論文、圖片和影片）轉換為結構化的持久化知識圖譜。它特別適合用於探索和理解大型程式碼庫的架構與檔案關係。該技能的核心功能包括建立「神節點」（god nodes）作為圖譜的頂層摘要，執行社群偵測以識別邏輯群組，並提供 query (查詢)、path (路徑) 和 explain (解釋) 三種工具來進行知識檢索與分析。當專案中存在 `graphify-out/` 目錄時，該技能會自動優先將使用者的問題作為圖譜查詢來處理，實現對程式碼庫深層結構的高效探索。支援 Claude Code、Coder、Codex 等主流 AI 代理平台，是開發者進行逆向工程、專案 onboarding 或複雜相依性分析的必備工具。
npx skills add https://github.com/geovanejunior92-debug/claude-skills/tree/main/skills/graphify用於回答任何關於程式碼庫、架構、檔案關係或專案內容的問題——尤其當 graphify-out/ 目錄存在時，應優先將其視為 graphify 查詢。能將任何輸入（程式碼、文件、論文、圖片、影片）轉換為帶有神節點、社群偵測以及查詢/路徑/解釋工具的持久化知識圖譜。
This repo contains 3 individual skills — each has its own dedicated page.
Compress natural language memory files (CLAUDE.md / AGENTS.md, todos, preferences) into caveman format to save input tokens. Preserves all technical substance, code, URLs, and structure. Compressed version overwrites the original file. Human-readable backup saved as FILE.original.md. Trigger: /caveman-compress FILEPATH or "compress memory file"
Close the loop on a Caveman learn report — review the ranked token sinks and apply cost-lowering fixes (trim config, offload recurring context to cavemem) with per-edit consent. Use when the user runs "caveman learn", asks to lower their agent's token cost, wants to trim a heavy CLAUDE.md / AGENTS.md, or wants to offload context they re-paste every session into cavemem.
Monitors task execution for skill improvement opportunities. Use this skill during ANY multi-step task, agentic workflow, or substantive work session where the agent is using tools and producing deliverables. It captures patterns, user corrections, workflow insights, and methodology worth preserving as reusable skills. Also triggers during post-task feedback discussions and when the user explicitly mentions skill observations, improvements, the observation log, skill taxonomy, or asks the agent to watch for skill opportunities. Also known as "One Skill to Rule Them All" — trigger on this phrase too. IMPORTANT: this skill should be invoked at the start of every task-oriented session — if you are about to use tools to produce deliverables, invoke this skill first. For reliable activation, pair this description with a CLAUDE.md / AGENTS.md instruction or harness-level session-start hook (see Recommended Activation Setup) — description-level matching alone is not enforceable.
Extract frames or short clips from videos using ffmpeg.
Summarize or transcribe URLs, YouTube/videos, podcasts, articles, transcripts, PDFs, and local files.
Use when testing, fixing, or extending the OpenClaw Control UI GUI with Vitest + Playwright end-to-end checks, mocked Gateway WebSocket flows, mocked dashboard runs, screenshots/videos, or agent-verifiable browser proof.
Obra superpowers agent skills.
See, Understand, Act on video and audio. See- ingest from local files, URLs, RTSP/live feeds, or live record desktop; return realtime context and playable stream links. Understand- extract frames, build visual/semantic/temporal indexes, and search moments with timestamps and auto-clips. Act- transcode and normalize (codec, fps, resolution, aspect ratio), perform timeline edits (subtitles, text/image overlays, branding, audio overlays, dubbing, translation), generate media assets (image, audio...
End-to-end marketing campaign planning and execution. Covers audience research, positioning, campaign angle definition, landing page copy, email sequences, social posts, ad copy, short-form video scripts, and content calendars. Use as the orchestration layer for multi-channel product launches. Use when planning or executing a multi-channel product launch, or producing landing page, email, social, or ad copy.