Install, update, version-check, or uninstall the Coco open-source AI workflow framework via bin/coco.js. Use when setting up Coco on a machine, checking out the pinned release tag into an existing clone, checking the installed version, or removing it. npx cocosuperintelligence is the published path (clones the pin and installs). Triggers on "install coco", "update coco", "set up coco", "coco cli", "uninstall coco".
インストール方法を見るインストールする前に、エージェントに与えられる指示の中身を確認できます。
Thin agent wrapper over bin/coco.js (package name cocosuperintelligence).
Drives the real CLI; does not reimplement it.
npx cocosuperintelligence is the published path: it clones the pinned
release tag and runs install. From a clone, invoke node bin/coco.js.
install / update check out the release tag matching package.json
(v1.5.0 today), not floating main.
| Command | Purpose | Invocation |
|---|---|---|
| (default) | clone + install, auto-detecting the adapter | node bin/coco.js |
install | clone + install with explicit flags | node bin/coco.js install [flags] |
update | check out the pinned release tag | node bin/coco.js update [dir] |
uninstall | remove symlinks + the clone | node bin/coco.js uninstall [dir] |
version | print version + check for updates | node bin/coco.js version |
--help | print usage | node bin/coco.js --help |
--adapter <name> — one of claude-code | cursor | grok | codex | generic--systems <list> — comma-separated, e.g. gsd,brain--dry-run — preview only, no writesnode bin/coco.js install --adapter cursornode bin/coco.js install --adapter groknode bin/coco.js install --systems gsd,brain --adapter claude-codenode bin/coco.js install --dry-runnode bin/coco.js updateThis CLI is human-output-oriented; it has no native --json mode. For agent use:
version prints cocosuperintelligence vX.Y.Z plus an update hint — parse the vX.Y.Z token.install.sh step failed — surface the captured stdout + stderr to the user.github.com only; on network failure the version check degrades quietly and the command still runs.install clones the pinned release tag and creates symlinks; uninstall removes them. install/update re-fetch, so they are not no-ops. Branch checkouts still git pull --ff-only and are not force-moved onto an older pin.github.com only. No telemetry. Disable update checks with COCO_NO_UPDATE_CHECK=1.node/npx, git, and bash. npx cocosuperintelligence is the published path (clones the pin and installs).まだレビューはありません。使ってみた感想をお寄せください。
概要と使いどころ
Train and optimize AI agents using Microsoft's Agent Lightning framework with reinforcement learning. Use when setting up agent training, instrumenting agents with tracing, configuring LightningStore, implementing reward functions, or optimizing prompts with RL/APO algorithms.
日本語の概要は準備中です。原文の説明を表示しています。
Post-run self-evaluation system that scores agent output on correctness, clarity, actionability, and conciseness. Use after /team runs, skill executions, or when explicitly asked to evaluate output quality.
日本語の概要は準備中です。原文の説明を表示しています。
Create AI marketing videos for ads, promos, product launches, and brand content. Models: Veo, Seedance, Wan, FLUX for visuals, Kokoro for voiceover. Types: product demos, testimonials, explainers, social ads, brand videos. Use for: Facebook ads, YouTube ads, product launches, brand awareness. Triggers: marketing video, ad video, promo video, commercial, brand video, product video, explainer video, ad creative, video ad, facebook ad video, youtube ad, instagram ad, tiktok ad, promotional video, launch video
日本語の概要は準備中です。原文の説明を表示しています。
Use when building AI features into a product: LLM integration, RAG pipelines, guardrails, streaming, AI UX, prompt engineering, or AI cost control. Treats prompts as code and validates every model output.
日本語の概要は準備中です。原文の説明を表示しています。
Your AI research and engineering brain trust. 59 named personas across 8 cells covering frontier labs, applied product, model architecture, reasoning/RL/agents, alignment and interpretability, theory and science of DL, multimodal and…
日本語の概要は準備中です。原文の説明を表示しています。
Use when designing a new REST or GraphQL API, reviewing an API spec before implementation, setting team API standards, or migrating REST to GraphQL. Covers resources, HTTP semantics, pagination, error handling, and pitfalls.
日本語の概要は準備中です。原文の説明を表示しています。