ステータス:0.x — 速報的な変更が予想されます。移行ガイドについては DEVELOPMENT.md をご覧ください。

共有エージェント学習のためのオープンスタンダード — AIエージェント同士のミスを繰り返さない構造化された知識です。

cqという用語は二つの由来に由来します。colloquy(/ˈkɒl.ə.kwi/)は、理解を促す構造化されたアイデアの交換です 一方通行の出力ではなく対話を通じて現れ、CQというラジオコールサイン(「任意の局、応答してください」)が同じモデルを捉えています。 オープンな招待、応答、そして相互作用を通じて構築された集合的な信号。どちらも同じ考えを捉えています:エージェントが放送する 彼らが学んだこと、そして他者がすでに知っていることに耳を傾けること。

全文は docs.mozilla.ai/cq をご覧ください。

設置

cq CLI(Homebrew、Scoop、GitHub Releases経由)をインストールし、その後コーディングエージェントにインストールします:

複数のホストに同時にインストールするには、--targetを繰り返します。

cq

Status: 0.x — expect breaking changes. See DEVELOPMENT.md for migration guides.

An open standard for shared agent learning — structured knowledge that prevents AI agents from repeating each other’s mistakes.

The term cq is derived from two sources: colloquy (/ˈkɒl.ə.kwi/), a structured exchange of ideas where understanding emerges through dialogue rather than one-way output, and CQ, a radio call sign (“any station, respond”), capturing the same model: open invitation, response, and collective signal built through interaction. Both capture the same idea: agents broadcasting what they’ve learned and listening for what others already know.

For the full documentation, visit docs.mozilla.ai/cq.

Installation

Install the cq CLI (via Homebrew, Scoop, or GitHub Releases), then install into your coding agent:

cq install --target 

Install into multiple hosts at once by repeating --target.

For per-host config paths, flags, remote-server setup, and Windows locations, see the installation guide.

Once installed, follow the Quickstart to verify it works and add your first knowledge unit.

How cq works in practice

You typically do not propose knowledge units manually. cq works through two agent workflows:

Skill-guided query/propose workflow

When your agent starts a task or encounters an error, the cq skill directs the agent to query the knowledge store before the agent retries.

If another agent has already solved this problem, your agent gets the relevant guidance immediately, instead of debugging from scratch.

If your agent discovers something that would save another agent time, for example:

• Undocumented API behavior
• Non-obvious workaround for a known issue
• Solution to an error that required multiple failed attempts to resolve

Then it will propose that learning as a knowledge unit.

Session reflection (optional)

/cq:reflect is a catch-all for the end of a session, useful if you suspect the agent missed proposing something in-flow. It scans the session for learnings worth sharing (debugging breakthroughs, undocumented API behavior, workarounds), presents them for approval, and queries the store before submitting each one to avoid duplicates.

The six MCP tools underneath: