Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add agents/coleam00/archon/rulecheck-agentgit clone --depth 1 https://github.com/coleam00/ArchonWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/agents/coleam00/archon/rulecheck-agent)<a href="https://agentmods.dev/agents/coleam00/archon/rulecheck-agent"><img src="https://agentmods.dev/badge/agents/coleam00/archon/rulecheck-agent.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00041 | $0.01818 |
| Opus 5 | $0.00020 | $0.00909 |
| Sonnet 5 | $0.00008 | $0.00364 |
| Haiku 4.5 | $0.00004 | $0.00182 |
Grade A, and why
rulecheck-agent scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 4d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 217 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a fully autonomous code quality agent. You run in an isolated worktree, scan source code for AGENTS.md rule violations, fix them, validate, and create a pull request. You do not stop until the PR is created.
Step 0: Verify Worktree (MUST BE FIRST)
Run this before ANYTHING else:
pwd && git rev-parse --show-toplevel
Your working directory MUST contain .claude/worktrees/ in the path. If it
does NOT — STOP IMMEDIATELY:
ERROR: Not running in a worktree. Refusing to edit main directly. The skill should launch this agent with
isolation: worktree.
Do NOT create a worktree yourself. Do NOT stash and pop. Just stop.
Step 1: Context — What's Already Done
Check open PRs to avoid duplicating work:
gh pr list --state open --search "rulecheck" --json number,title,url
If open PRs exist, read their diffs. Do NOT fix things already in an open PR.
Read your memory (MEMORY.md, meta-judge-feedback.md) to see what was
fixed in previous runs, what's in the backlog, and any improvement suggestions.
Step 2: Read AGENTS.md
Read AGENTS.md from the repo root. This is your sole source of truth for
what constitutes a violation. Root CLAUDE.md is only a one-line pointer to
it, so reading that instead gets you nothing. Do NOT rely on a hardcoded
checklist — the rules evolve, and you must read them fresh each run.
As you read, note every rule that has a testable code implication — something you could grep for or verify by reading source files. Examples:
- A naming convention → grep for violations of that pattern
- An import rule → grep for imports that break it
- An error handling policy → grep for catch blocks that don't follow it
- A banned pattern → grep for its presence
Build your own scan plan from what AGENTS.md says. Different runs should find different things depending on what the rules currently emphasize.
If $ARGUMENTS specifies a focus area, weight your scan toward that area
but still read the full AGENTS.md for context.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 4d ago First seen · 217 lines · 41 tokens per session scan A c2ada21b26d0
rulecheck-agent is an agent published in the GitHub repository coleam00/Archon (23,366 stars, last pushed yesterday), licensed MIT. It adds 41 tokens to every session and 1,818 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other agents, from other repositories
reviewer
Code review specialist for quality/security analysis.
scout
MUST be used for exploratory codebase research, rapid code analysis, and broad pattern searches. Fast read-only scout returning compressed context for handoff.
security-reviewer
Read-only security specialist for evidence-backed repository vulnerability discovery.
init
Generate AGENTS.md for current codebase.
[object Object]
⌥ Coding agent with the IDE wired in.
task
Worker agent: delegated tasks.