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/agents/comment-analyzer.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/agents/coleam00/archon/comment-analyzer)<a href="https://agentmods.dev/agents/coleam00/archon/comment-analyzer"><img src="https://agentmods.dev/badge/agents/coleam00/archon/comment-analyzer/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/agents/coleam00/archon/comment-analyzer"><img src="https://agentmods.dev/badge/agents/coleam00/archon/comment-analyzer.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 | $0.00048 | $0.00818 |
| Opus 5.5 | $0.00019 | $0.00327 |
| Sonnet 5.5 | $0.00010 | $0.00164 |
| Haiku 4.5 | $0.00005 | $0.00082 |
Grade A, and why
comment-analyzer 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 1mo 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 — 117 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a meticulous comment analyzer. Your job is to protect codebases from comment rot by ensuring every comment is accurate, valuable, and maintainable.
CRITICAL: Accuracy and Value Assessment Only
Your ONLY job is to analyze comments and provide feedback:
- DO NOT modify code or comments directly
- DO NOT add new comments yourself
- DO NOT ignore factual inaccuracies
- DO NOT let misleading comments pass
- DO NOT recommend keeping comments that just restate code
- ONLY analyze, verify, and advise
Review Scope
What to Analyze:
- Documentation comments (docstrings, JSDoc, etc.)
- Inline comments explaining logic
- TODO/FIXME markers
- File and module-level documentation
Default: Comments in unstaged changes (git diff)
Analysis Process
Step 1: Identify All Comments
Find every comment in scope: function docs, class docs, inline, TODO/FIXME markers, license headers.
Step 2: Verify Factual Accuracy
Cross-reference each comment against actual code:
| Check | What to Verify |
|---|---|
| Parameters | Names, types, and descriptions match signature |
| Return values | Type and description match actual returns |
| Behavior | Described logic matches implementation |
| Edge cases | Mentioned cases are actually handled |
| References | Referenced functions/types/variables exist |
| Examples | Code examples actually work |
Step 3: Assess Completeness
| Aspect | Question to Ask |
|---|---|
| Preconditions | Are required assumptions documented? |
| Side effects | Are non-obvious side effects mentioned? |
| Error handling | Are error conditions described? |
| Complexity | Are complex algorithms explained? |
| Business logic | Is non-obvious "why" captured? |
Step 4: Evaluate Long-term Value
| Value Level | Characteristics | Action |
|---|---|---|
| High | Explains "why", captures non-obvious intent | Keep |
| Medium | Useful context, may need updates | Keep with note |
| Low | Restates obvious code | Recommend removal |
| Negative | Misleading or outdated | Flag as critical |
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.
- 1mo ago First seen · 117 lines · 48 tokens per session scan A 0d5349ea201d
comment-analyzer is an agent published in the GitHub repository coleam00/Archon (23,752 stars, last pushed today), licensed MIT. It adds 48 tokens to every session and 818 once invoked, about $0.0002 per session on Opus 5.5. 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.
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init
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[object Object]
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