polis-protocol
Coordinate multi-vendor AI agents as a self-improving team — a learning router assigns work by track record and citizens can amend the protocol's own rules.
Best use case
polis-protocol is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Coordinate multi-vendor AI agents as a self-improving team — a learning router assigns work by track record and citizens can amend the protocol's own rules.
Teams using polis-protocol should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/polis-protocol/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How polis-protocol Compares
| Feature / Agent | polis-protocol | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Coordinate multi-vendor AI agents as a self-improving team — a learning router assigns work by track record and citizens can amend the protocol's own rules.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# Polis Protocol — a team of agents that develops ## Overview Most agent coordination is a passive board: claim a task, do it, mark it done. It records, but it never gets smarter, and its rules are frozen. Polis Protocol is the active alternative — a folder of markdown where each agent is a "citizen" with a capability card, work is routed by a learning bandit to whoever has the best track record on the task's tags, settled work files lessons that update the routing, and citizens can propose and vote on amendments to the protocol itself. It is vendor-agnostic: Antigravity, Claude, Codex, and Gemini agents can all share one `_polis/`. In Antigravity specifically, this turns Manager View's fixed pipeline into a team that learns who is actually best at each kind of work, instead of running the same roles in the same order every time. ## When to Use This Skill - Use when 2+ agents (especially across vendors) work on one project and "who should do this" is a real question. - Use when you want the team to measurably improve over time — routing that adapts from outcomes, not static role labels. - Use when you need a durable, git-auditable record of who did what, what was learned, and which rules changed. - Use when Antigravity's default orchestration is too rigid and you want routing + governance on top of it. ## How It Works ### Step 1: Found a polis Run the published CLI — `uvx` fetches the latest release from PyPI ([polis-protocol](https://pypi.org/project/polis-protocol/)), so you always get the current version: ```bash uvx polis-protocol init \ --project-root . \ --agent-id gemini-antigravity-yourproject \ --vendor google --model gemini-3 --tool antigravity ``` (Prefer a pinned, reviewed install? `pipx install polis-protocol==<version>`, or clone the repo and run `python3 scripts/init_polis.py` with the same flags.) This writes `_polis/` plus the skill into `.agents/skills/` (the path Antigravity reads), and bridge pointers (`GEMINI.md`, `AGENTS.md`) that point every tool at `_polis/CONSTITUTION.md`. Tip: add `--dry-run` to preview every file before anything is written; init never overwrites existing files, and `polis init --repair` restores missing ones. ### Step 2: Register citizens and open contracts Each agent publishes a capability card under `_polis/citizens/`. Work is opened as a contract with `required_tags`, not assigned to a fixed role. ### Step 3: Route by track record ```bash polis route --polis-root _polis \ --contract _polis/contracts/open/your-task.md --explain ``` The router prints a score breakdown (history / self-rating / cost / availability / applied lessons) and recommends the citizen with the strongest record on the task's tags. Agents can also reserve files (`polis reserve src/auth --as <citizen>`) so two agents never edit the same path at once — overlapping claims are rejected with the holder named. ### Step 4: Settle, learn, and amend ```bash polis contract settle <contract-id> --quality 5 polis reconcile --polis-root _polis ``` A settled contract files a lesson; accepted lessons carry a bounded `routing_effect` the router reads — and names in `--explain` — on the next similar task. Failures become guardrails (`polis guardrail add …`) that future contracts on those tags inherit as must-pass acceptance criteria. When a rule stops working, a citizen proposes an amendment and the others vote. Reproduce the learning claim yourself: `polis bench --mode learning`. ## Examples ### Example 1: See the team learn (no install, 30 seconds) ```bash git clone https://github.com/yehudalevy-collab/polis-protocol.git cd polis-protocol git checkout <reviewed-commit-sha> bash scripts/demo.sh ``` The router recommends Gemini for a Spanish-translation contract — because settled work taught it she has the best record on that tag, not because anyone reassigned it. ### Example 2: Explain any routing decision ```bash python3 scripts/route_contract.py --polis-root examples/research-team/_polis \ --contract examples/research-team/_polis/contracts/open/parent-newsletter-issue-3.md --explain ``` ## Notes - No server, no runtime, no database — the whole protocol is markdown plus two small Python scripts. - Vendor-agnostic by design; a Claude or Codex agent can join the same polis an Antigravity agent created. - Full Antigravity integration guide: https://github.com/yehudalevy-collab/polis-protocol/blob/main/docs/antigravity.md ## Limitations - Routing quality depends on accurate citizen capability cards and enough settled work history to learn from. - The protocol coordinates agent work but does not replace review, tests, or explicit maintainer approval. - Multi-agent voting and amendments can add process overhead for small, single-owner tasks. - The upstream scripts are external code; pin to a reviewed commit and run `--dry-run` before allowing writes to a project.
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