Fallow is a command-line static-analysis tool that builds a dependency graph of TypeScript and JavaScript code to identify unused code, duplication, circular dependencies, complexity hotspots, boundary violations, and styling drift. It is for developers reviewing codebases and verifying changes, with catalogue entries that add agent, editor, and workflow integrations.
Borrowing it
Nothing to install: this file belongs to fallow-rs/fallow. 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/fallow-rs/fallow/main/.agents/skills/review/SKILL.mdgit clone --depth 1 https://github.com/fallow-rs/fallowWrote 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/skills/fallow-rs/fallow/review)<a href="https://agentmods.dev/skills/fallow-rs/fallow/review"><img src="https://agentmods.dev/badge/skills/fallow-rs/fallow/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/skills/fallow-rs/fallow/review"><img src="https://agentmods.dev/badge/skills/fallow-rs/fallow/review.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00029 | $0.00349 |
| Opus 5.5 | $0.00012 | $0.00140 |
| Sonnet 5.5 | $0.00006 | $0.00070 |
| Haiku 4.5 | $0.00003 | $0.00035 |
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 28d 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
Review
- Re-read
AGENTS.md, the active plan, the current branch, and the complete diff against its intended base. - Run the applicable gates in
docs/development/quality-gates.md. - Select reviewers using
docs/development/review-routing.md. - Review public contracts, all affected output formats, filters, integrations, generated surfaces, security boundaries, and companion parity.
- When runtime behavior changed, run the behavior comparison on public
projects from
docs/development/quality-gates.mdand explain every difference. When the change rejects input that was accepted before, also run the full analysis on a rejected input and read every finding, not only the diagnostic. - Filter reviewer findings before you act on them:
- trace the call site before you accept a bug claim;
- drop style preferences and "a different design would also work";
- check the diff or output that a reviewer cites, not its summary;
- mark each accepted claim with its proof level. Record dismissed findings with a one-line reason in the verification notes. More than about five blocks usually means the filter is too weak.
- Classify each result as
APPROVE,CONCERN, orBLOCK. - Fix every block, rerun the blocking reviewer, and update verification.
Review the actual source and live output. Do not infer correctness from a green compile, a narrow unit test, or a previously cached report.
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 28d ago Changed · +2 lines 9121cde436f2
- 1mo ago Changed · +9 lines 69377f31c2a0
- 2mo ago First seen · 20 lines · 29 tokens per session scan A 0bdc70f4160d
review is a skill published in the GitHub repository fallow-rs/fallow (5,273 stars, last pushed today), licensed MIT. It adds 29 tokens to every session and 349 once invoked, about $0.0001 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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argot-review-pr
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argot-write-rule
Codify a repo convention argot's built-ins don't cover into a scripted custom rule — a .argot/rules/NAME/rule.toml manifest plus a sandboxed Rhai script that fires exactly like a built-in, gated on a green fixture suite before it ever sees a real diff. Use when the user asks to "write an argot rule for X", "codify…
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argot-suggest-rules
Turn a convention argot has already discovered into a scripted custom rule. Runs argot conventions, surfaces the repo's mined placement conventions (where a kind of code lives — "validation in schema files", "DB access only in migrations", "business logic in the service layer, not views") and internal-API vocabulary…