create-rule
Create Cursor rules for persistent AI guidance. Use when the user wants to create a rule, add coding standards, set up project conventions, configure…
Start a safe, governed autonomous loop from a plain-language goal. Use when the user says /coco-loop, "run an autonomous loop", "keep my build green for N hours", "work on X autonomously for a while", or wants a bounded self-improving loop that proposes fixes and never commits
$ npx -y skills add coco-research/coco --skill coco-loop --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/coco-loopContext preview
The summary Claude sees to decide when to auto-load this skill.
Start a safe, governed autonomous loop from a plain-language goal. Use when the user says /coco-loop, "run an autonomous loop", "keep my build green for N hours", "work on X autonomously for a while", or wants a bounded self-improving loop that proposes fixes and never commits
name: coco-loop description: > Start a safe, governed autonomous loop from a plain-language goal. Use when the user says /coco-loop, "run an autonomous loop", "keep my build green for N hours", "work on X autonomously for a while", or wants a bounded self-improving loop that proposes fixes and never commits on its own. Turns a vague goal into a readable charter the user confirms, then arms and runs the loop propose-only under the coco-loops governance framework. domain: meta
Turn a plain-language goal into a governed, propose-only loop. You compile the goal into a charter, the person confirms it, and the loop runs under the coco-loops framework: it proposes changes, a separate verifier judges them, and nothing is committed. The loop stops itself when its lifetime cap of active work is spent.
The framework enforces an immutable constitution underneath every charter. You cannot write a charter that disables the verifier, commits without approval, edits the constitution, sends content to raw public-cloud endpoints, or runs unattended destructive operations. The `coco-loops charter` command rejects any charter that tries. Do not attempt to work around it. Present the floor to the person as a feature.
`coco-loops` must be on the PATH. Install it from [coco-research/coco-loops](https://github.com/coco-research/coco-loops):
git clone https://github.com/coco-research/coco-loops pip install -e coco-loops
Check with `coco-loops --help`. If it is missing, tell the person how to install it and stop.
Read the person's goal. Ask at most one or two clarifying questions, and only when the answer genuinely changes the charter:
so a dedicated worktree is strongly recommended (the loop reverts its own changes each cycle and refuses to run on a dirty tree, to avoid clobbering uncommitted work).
`4h`. The clock only advances while the loop is actually working, so a closed laptop or an idle wait does not burn it.
Do not over-question. If the goal is clear, proceed.
Get the exact field list with `coco-loops charter --schema`, then produce a charter as JSON. Derive the principles from the goal, and add sensible safe defaults. Keep principles readable: they are what the person confirms and what we audit the loop against.
Example, for "keep my frontend build green for the next 4 hours":
{
"loop_id": "keep-build-green",
"objective": "Make failing frontend tests pass and keep the build green.",
"principles": [
"Only touch code covered by a failing test; keep the diff as small as possible.",
"If a test is genuinely stale, propose updating it rather than weakening it silently.",
"Prefer fixing the code over changing the test when a real regression is likely."
],
"guardrails": [
"No dependency or lockfile changes.",
"No CI or build-config edits."
],
"context": ["the frontend test suite"],
"inputs": ["failing tests detected each cycle"],
"lifetime": "4h",
"level": "L1"
}Rules for the charter you produce:
the promotion gate, never declared here.
Write the charter JSON to a temporary file, then run:
coco-loops charter --from-json <file>
This validates the charter against the constitution floor and prints a readable version. If validation fails, it prints why (with the invariant it violated); fix the charter and try again. Show the rendered charter to the person and ask them to confirm before anything is armed.
On confirmation:
coco-loops charter --from-json <file> --install
This writes `<loop_id>.contract.md` into the loops directory, arms the lifetime cap, and clears the kill-switch. The loop is now defined and armed, propose-only.
The loop reads tasks from a JSON queue (a list of `{"id", "name", "instruction"}` objects). Seed the queue with concrete, grounded tasks, for example one task per failing test with the file and the assertion. A loop is only as good as its task list; vague tasks produce no-ops.
Run it in the chosen worktree:
coco-loops run <loop_id> --repo <worktree> --tasks <queue.json>
Each cycle it pops a task, asks the maker (cursor-agent by default) to propose a change, has the verifier judge it, logs the proposal, and reverts the tree. Use `--once` to run a single cycle first and watch what it does. Recommend a dedicated worktree so the loop's revert can never touch the person's uncommitted work.
coco-loops status <loop_id>
shows the recent proposals, the verifier verdicts, and how much of the lifetime is spent. Everything is propose-only: the person reviews the batch of proposals and applies what they want. When the lifetime is spent the loop stops itself. To run another session, re-arm with `coco-loops start <loop_id> --for <duration>` (or run `charter --install` again).
CoCo Super Intelligence is the orchestration layer that turns Claude Code, Cursor, or Codex into an engineering department: a routed advisory board, 185 skills, 280 commands, persistent state. Local. Open-core — MIT core; Super Intelligence is proprietary, own-use.
Repo: coco-research/coco
Create Cursor rules for persistent AI guidance. Use when the user wants to create a rule, add coding standards, set up project conventions, configure…
Guides users through creating effective Agent Skills for Cursor. Use when the user wants to create, write, or author a new skill, or asks about skill…
Create custom subagents for specialized AI tasks. Use when the user wants to create a new type of subagent, set up task-specific agents, configure code…
Convert 'Applied intelligently' Cursor rules (.cursor/rules/*.mdc) and slash commands (.cursor/commands/*.md) to Agent Skills format (.cursor/skills/). Use…
Modify Cursor/VSCode user settings in settings.json. Use when the user wants to change editor settings, preferences, configuration, themes, font size, tab…
Train and optimize AI agents using Microsoft's Agent Lightning framework with reinforcement learning. Use when setting up agent training, instrumenting agents…