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/slop-audit/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/slop-audit)<a href="https://agentmods.dev/skills/fallow-rs/fallow/slop-audit"><img src="https://agentmods.dev/badge/skills/fallow-rs/fallow/slop-audit/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/slop-audit"><img src="https://agentmods.dev/badge/skills/fallow-rs/fallow/slop-audit.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 | $0.00040 | $0.00725 |
| Opus 5.5 | $0.00016 | $0.00290 |
| Sonnet 5.5 | $0.00008 | $0.00145 |
| Haiku 4.5 | $0.00004 | $0.00072 |
Grade A, and why
slop-audit 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 23d 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 — 68 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Slop audit
Use the native implement lifecycle for accepted changes, including its ready
PR requirement. Finish with review, ship when authorized, and sweep.
Read docs/development/repo-map.md to choose concrete ownership boundaries.
Evidence before cleanup
Maintain a temporary ledger outside tracked files. For a repository-wide pass, cover the analyzer pipeline, engine/API/output/CLI, protocol hosts, editor and web consumers, packaging/sidecars, and maintenance tooling. Inspect these axes within each relevant domain:
- tests: tautologies, shadow implementations, unreachable assertions, weak failure injection, and duplicate behavior coverage;
- abstractions: forwarding wrappers, test-only seams, speculative options, duplicated normalization or derived state;
- runtime cost: avoidable owned copies, intermediate collections, repeated work;
- failure behavior: swallowed errors, stale fallbacks, lifecycle and cleanup;
- ownership: public contracts, dynamic entrypoints, security/release boundaries;
- maintenance: obsolete comments, copied catalogues, dead routes and dependencies.
Record exact paths, real callers, the proposed simplification, retained behavioral coverage, and validation evidence. Distinguish inspected/no-change from unexamined or blocked areas. A search hit is a hypothesis, not a finding. Use disjoint subagents for independent domains when available, then have a reviewer challenge both accepted changes and plausible no-change decisions.
Before removing a test, establish which executed assertion implies its useful
contract. For misleading tests, inject a realistic production fault and show
that the old test accepts it while the replacement rejects it. Keep the
replacement on the runtime path, not a second implementation in test code.
Similar bodies, assertion counts, or deletion targets do not prove redundancy.
Apply the test evidence rules in docs/development/quality-gates.md to each
kept or replacement test.
A comment that explains a surprise in the code flags that symbol for a refactor: make the code clear, then remove the comment. When you are not sure about a comment, flag it in the ledger. Do not delete it.
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.
- 23d ago Changed · +6 lines bbadae298a87
- 1mo ago First seen · 62 lines · 40 tokens per session scan A 9c50097e33d3
slop-audit is a skill published in the GitHub repository fallow-rs/fallow (5,139 stars, last pushed today), licensed MIT. It adds 40 tokens to every session and 725 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 2026-09-07.
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Use when you want to verify compiler changes and commit with the correct convention. Runs tests, lint, and format, then commits with the [compiler] or [rust-compiler] prefix.
review-work
Post-implementation gate review: run manual QA on the real surface yourself, then launch ONE gate reviewer (never a panel) to audit goal, constraints, code quality, security, missed context, and QA evidence. Use before a PR handoff or when the user explicitly asks to review completed work.
brooks-sweep
Full-sweep mode: runs a unified analysis across all quality dimensions — code decay, architecture, tech debt, and test quality — then applies fixes directly to the codebase. Safe changes are auto-applied; risky changes are confirmed before execution. Drawing on twelve classic engineering books. Triggers when: user…
brooks-test
Test quality review drawing on twelve classic engineering books — with primary focus on xUnit Test Patterns, The Art of Unit Testing, How Google Tests Software, and Working Effectively with Legacy Code — that diagnoses structural problems in an existing test suite: brittleness, mock abuse, coverage illusions, slow…