With Monet — independently scanned and version-tracked by SaferSkills.
SaferSkills independently audited With Monet (Agent Skill) and scored it 92/100 (green). The audit ran 55 deterministic rules across Security, Supply Chain, Maintenance, Transparency, and Community; it found 0 high-severity and 2 lower-severity findings. The full rule-by-rule trace and per-finding evidence are below. Free, methodology-open.
Findings & checks · 2 flagged
The text {match} tells the agent to skip the normal "ask the user first" gate. Used adversarially it removes the human-in-the-loop check before destructive or sensitive actions, turning a normally-gated agent into a fire-and-forget executor.
The text {match} tells the agent to skip the normal "ask the user first" gate. Used adversarially it removes the human-in-the-loop check before destructive or sensitive actions, turning a normally-gated agent into a fire-and-forget executor.
Every scanned point with the score it earned and what moved between them.
First recorded scan — no prior version to compare against.
The primary manifest — the file an agent reads to learn what this artifact does.
An agent-agnostic harness that pairs a state-centric coding lead (`Stig`) and a focused worker team with [Monet](https://www.npmjs.com/package/@team-monet/monet)'s memory substrate.
The substrate — the monet MCP server + CLI (available as @team-monet/monet on npm) — maintains a persistent memory model so the agent doesn't have to. with-monet is the lightweight harness that points the coding agent you already use (Claude Code) at that substrate and gives it a team that knows how to use it.
| Repo | What it is |
|---|---|
team-monet/monet | Monet — the local-first client: the monet MCP server + CLI (npm @team-monet/monet). |
| `with-monet` (this repo) | The lightweight, agent-agnostic harness: portable agent prompts + bootstrap that wire a host to monet. |
`Stig` is a state-centric lead — the memory discipline (extract → review → commit) is now structural in Monet, so Stig's prompt stays lean and focuses on assembling context for the worker team rather than bookkeeping its own memory.
agent_context (prewarm), delegates with pre-assembled context, and is the only agent that touches Monet.explorer, researcher, analyst, developer, tester, reviewer, auditor, security, reliability, aria.You don't clone this repo or run a script. You open the coding agent you already use, paste one line, and the agent installs and configures Monet for you — detecting your host, wiring the monet MCP server, installing the team, offering to seed memory from your existing docs, then offering to start. It diagnoses and fixes failures interactively, and adapts to your preferences.
Paste into your agent:
Set up Monet globally (for all my projects): read https://raw.githubusercontent.com/team-monet/with-monet/main/bootstrap/install.md and follow it, checking with me at each decision point.
_(Local dev: point at with-monet/bootstrap/install.md instead of the URL. The substrate it installs — monet — ships on npm as @team-monet/monet.)_
Already installed? To update your existing Monet install, paste:
Can you update my Monet installation following https://raw.githubusercontent.com/team-monet/with-monet/main/bootstrap/install.md?
The agent then follows the bootstrap playbook: orient → get Monet → configure the MCP server → install the team → offer memory ingest → offer to start. Why agent-first: the agent already has tools in your environment, so it can install, verify, and recover from failures conversationally — and we can tailor the experience to each user.
⭐ Like Monet? [Star this repo](https://github.com/team-monet/with-monet) to support it — and Watch → Custom → Releases to get notified of new versions.
~30 seconds. Free. No account. Every finding cites a rule and a line of evidence.