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.
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.
git 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-seams)<a href="https://agentmods.dev/commands/coleam00/archon/review-seams"><img src="https://agentmods.dev/badge/commands/coleam00/archon/review-seams/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-seams"><img src="https://agentmods.dev/badge/commands/coleam00/archon/review-seams.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 | $0.00000 | $0.02419 |
| Opus 5.5 | $0.00000 | $0.00968 |
| Sonnet 5.5 | $0.00000 | $0.00484 |
| Haiku 4.5 | $0.00000 | $0.00242 |
Grade A, and why
review-seams scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured today.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 56 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Seam Review — Missing Types at Boundaries
Hunt this defect class wherever the change exposes it, in any language: a type is missing at a seam, and something downstream pays for it — a parser that mis-reads, a hand-synced copy of a set, type, or table whose owner it could import or derive from, a second route that skips the validator, a value that silently loses fields across a re-entry. Read-only: never modify files, commit, or post anywhere. Never edit this checkout, not even to revert: sibling reviewers read it at the same time, and the engine fails a reviewer that leaves it changed. Try a mutation in a scratch worktree under this run (git worktree add --detach "$(mkdir -p "$ARTIFACTS_DIR/scratch/seams" && mktemp -d "$ARTIFACTS_DIR/scratch/seams/XXXXXX")" HEAD; the workflow removes it), and before running anything there, install its dependencies with the project's own package manager in locked mode, never updating a lockfile. Any other scratch file you write — a probe script, a note, captured output — goes under $ARTIFACTS_DIR, never in this checkout.
Read $ARTIFACTS_DIR/review/scope.md first. The project's own values are in its steering documents: open, where the project has them, its architecture.md, its engineering.md, and its direction document — at the root, in a config directory such as .archon/, or wherever its steering files point — only when a finding depends on a value one of them states, and read the section you cite, not the whole file. A preference one of them states is a finding you cite, and one none of them states is taste you leave out. Anchor the review on the accepted work order's stated invariants, and apply the supplied full-review policy: $mode.output.risks. In light mode, scope.md names the prior report and the correction delta: read the prior report and $ARTIFACTS_DIR/implementation.md, judge each prior finding assigned to this lens as resolved by the delta, validly declined (the implementer's evidence holds), or still open, then examine only the delta.
A seam is where a value crosses to something that must interpret it: serialization, process/language boundaries, events, persisted formats, pause/resume re-entry, load-time→run-time handoffs. A plain function call is not a seam.
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 Changed · +3 lines 6ad59c32e0eb
- yesterday Changed 542759e55ebc
- 10d ago Changed 225156d881c7
- 11d ago Changed ad283051a6cc
- 1mo ago First seen · 53 lines · 0 tokens per session scan A edecc7b36122
review-seams is a command published in the GitHub repository coleam00/Archon (23,690 stars, last pushed today), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 2,419 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
review-prs
Parallel PR triage: decide merge-worthiness, prepare rebased worktrees, fix blockers, return them for human merge.
fix-issues
Diagnose, reproduce, then fix reproducible open GitHub issues in parallel: one clean worktree/issue; symlink build artifacts to avoid rebuilds.
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-pr-resolve
Read open PR comments, evaluate each against current code via the rigor contract, implement accepted findings, reply inline. Multi-platform.