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/.github/prompts/review.prompt.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)<a href="https://agentmods.dev/commands/coleam00/archon/review"><img src="https://agentmods.dev/badge/commands/coleam00/archon/review/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/commands/coleam00/archon/review"><img src="https://agentmods.dev/badge/commands/coleam00/archon/review.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00015 | $0.01059 |
| Opus 5 | $0.00008 | $0.00530 |
| Sonnet 5 | $0.00003 | $0.00212 |
| Haiku 4.5 | $0.00002 | $0.00106 |
Grade A, and why
review 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 today.
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 — 212 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Code Review
Input: ${input:scope}
Your Mission
Perform a thorough code review:
- Understand what you're reviewing and its purpose
- Check the code against project patterns
- Run validation (type-check, lint, tests)
- Identify issues by severity
- Report findings
Golden Rule: Be constructive and actionable. Every issue should have a clear recommendation.
Phase 1: DETERMINE SCOPE
Parse Input
| Input Type | Example | Action |
|---|---|---|
| PR number | 123, #123 |
Fetch PR diff with gh pr diff 123 |
| PR URL | github.com/.../pull/123 |
Extract number, fetch PR diff |
| File path | src/api/flags.ts |
Review single file |
| Folder path | server/src/ |
Review all files in folder |
| Blank | (none) | Review unstaged git changes |
Get Review Target
For PR:
gh pr view {NUMBER} --json number,title,author,files
gh pr diff {NUMBER}
For file/folder:
find {path} -name "*.ts" -o -name "*.tsx" | grep -v node_modules
For blank (unstaged changes):
git diff --name-only
git diff
Phase 2: CONTEXT
Read Project Rules
- Read
copilot-instructions.mdfor project conventions - Understand the patterns in the codebase
Understand Intent
- For PRs: Read title and description
- For files: Understand the file's purpose in the codebase
- For changes: What was modified and why?
Phase 3: REVIEW
Review Each File
For each file in scope, check:
| Category | Check |
|---|---|
| Correctness | Does the code work as intended? |
| Type Safety | Are types explicit, no implicit any? |
| Patterns | Does it follow existing codebase patterns? |
| Error Handling | Are errors handled appropriately? |
| Tests | Are there tests for this code? |
Categorize Issues
| Severity | Criteria |
|---|---|
| Critical | Security issues, data loss, crashes |
| High | Type violations, missing error handling, logic errors |
| Medium | Pattern inconsistencies, missing edge cases |
| Low | Style suggestions, minor improvements |
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.
- today First seen · 212 lines · 15 tokens per session scan A 92f0a17aa345
review is a command published in the GitHub repository coleam00/Archon (23,398 stars, last pushed today), licensed MIT. It adds 15 tokens to every session and 1,059 once invoked, about $0.0001 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 2026-09-08.
Other commands, from other repositories
review-prs
Parallel PR triage: decide merge-worthiness, prepare rebased worktrees, fix blockers, return them for human merge.
review
System prompt for /review slash command.
cleanup
Autonomous cleanup-loop iteration: discover ONE target → complete execution → verify → report. Runs stateless: derive from current tree; assume prior runs left it consistent.
review
Run code review on files or recent changes.
factory-ticket
Implement exactly one already-claimed Linear ticket in the current worktree.
refactor-clean
Remove dead code, duplicates, and tech debt with safe automated cleanup.