en un clic
caveman
Use this skill when >
Installer avec Codex ou Claude Copiez ce prompt, collez-le dans Codex, Claude ou un autre assistant, puis laissez-le vérifier la page du skill et l'installer pour vous.
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Use this skill when >
Installer avec Codex ou Claude Copiez ce prompt, collez-le dans Codex, Claude ou un autre assistant, puis laissez-le vérifier la page du skill et l'installer pour vous.
Basé sur la classification professionnelle SOC
Assist with Colibri: pure-C LLM inference engine for running GLM-5.2 (744B MoE) on consumer machines with ~25 GB RAM. Use when setting up, building, converting models, running inference, configuring expert streaming and caching, optimizing speculative decoding (MTP), GPU integration, and integrating Colibri into production pipelines. Includes build setup, model download & conversion, chat/inference modes, performance tuning, and API integration patterns.
Discover and apply curated prompts from the prompts.chat collection to optimize AI interactions. Use when refining prompt engineering, finding domain-specific prompt templates, improving response quality, or building prompt-based workflows. Triggers on: prompt optimization, prompt templates, prompt engineering, prompt library, curated prompts, prompt discovery, and AI prompt patterns.
Turn ONE topic into a finished Vox-style paper-collage explainer / ad video, end to end on the Atlas Cloud API + local ffmpeg — script, collage keyframes, motion, voice-over, music, captions, all automated. Use this whenever the user wants a "Vox style" video, a paper/torn-paper collage animation, a "motion collage", a narrated explainer or short ad built from AI-generated collage posters, a scrapbook-style tribute, or wants to turn a topic / product / person into a punchy narrated collage video — even if they don't say the word "Vox". Also use when reproducing Stav Zilber / rom1trs / Higgsfield-style collage ad workflows, or when the user asks for a motion collage or a scrapbook-style tribute. Triggers: "vox video", "collage video", "motion collage", "paper collage explainer", "make a collage ad", "turn this topic into a collage video".
Assist with Motion Previs Studio v4: a cross-platform desktop app for AI-film previsualization. Use when setting up, configuring, troubleshooting, or extending motion-previs-studio for pose extraction, depth mapping, camera motion solving, control layer export, and bundle production for AI-video workflows (Seedance, ComfyUI, Blender, Runway, Kling). Includes build setup, feature integration, UI/logic debugging, and export pipeline optimization.
Work with Lapian Notes / 拉片笔记 (github.com/bkingfilm/lapian-notes) — a local- first React/Vite tool that turns a film into an editable shot-by-shot study notebook: local frame extraction, AI-assisted structure analysis (bring your own AI, no API key required), story-line swimlane timeline, structure tree, and audience-emotion curve. Use when the user asks about Lapian Notes, "拉片笔记", "拉片" (shot-by-shot film analysis) tooling, cloning/running this repo (npm run dev, run.bat/run.command), the AI-analysis-package (ZIP) round-trip workflow, or contributing a PR to lapian-notes. Not for generic video editing (use `opencut` for that) or generic film-analysis theory unrelated to this codebase.
Set up, run, and contribute to TokHub (github.com/yaojingang/TokHub) — an open-source AI API relay monitoring, recommendation, and OpenAI-compatible gateway system with L1/L2/L3 channel health probing, usage metering, alerts, audit, and Docker self-hosting. Use when the user asks about TokHub, "AI API 中转站监控", cloning/running the Go + React monorepo (TOKHUB_ROLE, sqlc, TimescaleDB, NATS), the L1/L2/L3 probe algorithm, the OpenAI-compatible `/gateway/v1/*` endpoint, or contributing a PR to TokHub. Do not use for connecting a running agent to a live TokHub instance's own API (that is covered by the project's own bundled `agent-skills/tokhub` skill inside the TokHub repo, not this one).
| name | caveman |
| description | Use this skill when > |
| compatibility | > |
| allowed-tools | Read Grep Glob Bash Write Edit |
| metadata | {"tags":"token-reduction, communication, brevity, compression, productivity","platforms":"Claude, ChatGPT, Gemini, Codex","version":1,"source":"mattpocock/skills"} |
Ultra-compressed communication. ~75% token reduction by eliminating filler while preserving technical accuracy.
Triggers: "caveman mode", "talk like caveman", "use caveman", "less tokens", "be brief", /caveman
Deactivation: "stop caveman" or "normal mode"
Drop:
Use:
[thing] [action] [reason]. [next step].Keep unchanged:
Active every response once triggered. No reverting or drift until explicitly stopped.
Resume caveman mode after the exception is handled.
React performance issue:
Normal: "The reason your component is re-rendering so frequently is that you're creating a new object literal as a prop on every render, which causes React to see it as a new reference each time." Caveman: "Inline obj prop → new ref → re-render.
useMemo."
Database connection:
Normal: "A connection pool allows you to reuse existing database connections rather than creating new ones, which avoids the overhead of the TCP handshake and authentication process, resulting in better performance under load." Caveman: "Pool = reuse DB conn. Skip handshake → fast under load."
.agent-skills/skill-standardization/SKILL.md.agent-skills/skill-standardization/scripts/validate_skill.sh