Archon is a workflow engine for AI coding agents that turns development processes into YAML-defined sequences with phases, validation gates, and artifacts. Developers use it to run repeatable processes such as planning, implementation, testing, code review, and pull-request creation across projects. The catalogue entries provide commands, agents, skills, hooks, instructions, and settings for working with Archon.
Borrowing it
Nothing to install: this file belongs to coleam00/Archon. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/coleam00/Archon/dev/.claude/commands/review-doc.mdgit 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/commands/coleam00/archon/review-doc)<a href="https://agentmods.dev/commands/coleam00/archon/review-doc"><img src="https://agentmods.dev/badge/commands/coleam00/archon/review-doc.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 5.1 | $0.00000 | $0.00379 |
| Opus 5 | $0.00000 | $0.00189 |
| Sonnet 5 | $0.00000 | $0.00076 |
| Haiku 4.5 | $0.00000 | $0.00038 |
Grade A, and why
review-doc 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 6d 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.
What it actually says
Documentation Review
Review the document at $ARGUMENTS for clarity, consistency, and simplicity.
DO NOT make any edits yourself - only report findings.
Review Focus
1. Clarity & Readability
- Are there sections that are confusingly worded or hard to understand?
- Are there redundant explanations that could be consolidated?
- Is the document structure logical and easy to navigate?
- Are there unnecessary complications in the explanations?
2. Consistency
- Do the code snippets match the described behavior?
- Are terms used consistently throughout (e.g., same concept called different names)?
- Do numbers/values match across sections (e.g., limits, timeframes)?
- Are behaviors described consistently across different sections?
3. Simplicity
- Are there over-engineered solutions described that could be simpler?
- Are there unnecessary abstractions or complexity?
- Could any diagrams or tables be simplified without losing meaning?
- Are there sections that explain obvious things unnecessarily?
4. Completeness
- Are there gaps in the implementation details?
- Are edge cases addressed?
- Is there enough detail for someone to implement from this doc?
Your Deliverable
Provide a structured report with:
-
Summary: Overall assessment (1-2 sentences)
-
Issues Found: Specific problems with location (section/line reference)
- Categorize as Critical, Moderate, or Minor
-
Suggestions: Concrete improvements (but don't make the edits)
-
Questions: Anything unclear that needs clarification from the author
Guidelines
- Read the ENTIRE document carefully
- DO NOT edit the file directly
- Only report findings
- Be constructive and specific
- Focus on making the document better for future readers/implementers
- Prioritize issues that would cause confusion or implementation problems
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.
- 6d ago First seen · 53 lines · 0 tokens per session scan A abb4fd9a2c34
review-doc is a command published in the GitHub repository coleam00/Archon (23,389 stars, last pushed 3d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 379 tokens. 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 commands, from other repositories
fix-issues
Diagnose, reproduce, then fix reproducible open GitHub issues in parallel: one clean worktree/issue; symlink build artifacts to avoid rebuilds.
review-prs
Parallel PR triage: decide merge-worthiness, prepare rebased worktrees, fix blockers, return them for human merge.
triage
Classify/label newly opened GitHub issues missing labels.
release
Release all packages at specified version.
cleanup
Autonomous cleanup-loop iteration: discover ONE target → complete execution → verify → report. Runs stateless: derive from current tree; assume prior runs left it consistent.
hatch3r-benchmark
Run and analyze performance benchmarks. Compare results against baselines, identify regressions, and produce performance reports.