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.
npx skills add stuartshields/claude-setup --skill module-depth-reviewgit clone --depth 1 https://github.com/stuartshields/claude-setupWrote 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/stuartshields/claude-setup/module-depth-review)<a href="https://agentmods.dev/skills/stuartshields/claude-setup/module-depth-review"><img src="https://agentmods.dev/badge/skills/stuartshields/claude-setup/module-depth-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/stuartshields/claude-setup/module-depth-review"><img src="https://agentmods.dev/badge/skills/stuartshields/claude-setup/module-depth-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 | $0.00121 | $0.02246 |
| Opus 5.5 | $0.00048 | $0.00898 |
| Sonnet 5.5 | $0.00024 | $0.00449 |
| Haiku 4.5 | $0.00012 | $0.00225 |
Grade A, and why
module-depth-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 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 — 202 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Module depth review
Find shallow modules. Propose deep ones.
A shallow module has an interface nearly as complex as its implementation — it forces callers to learn a lot for little behavioural payoff. A deep module hides substantial behaviour behind a small interface. This skill audits a region of the codebase against that lens and proposes consolidations.
This is an audit skill. It produces findings and proposals — never edits. Pair with audit-vs-fix-discipline for the output discipline.
When to use
Apply when the user asks about module boundaries, file organisation, or "is this over-modularised?". Concrete triggers:
- "Is this folder doing too much / too little?"
- "Should these be one module?"
- "Too many small files for one concept"
- "The interface is as complex as the implementation"
- "Review the architecture of X" (where X is a feature or subsystem, not the whole app)
Not the right skill for:
- Tactical complexity inside a function — use
simplify - Removing dead code or orphans — use
cleanup - Whole-app architecture decisions — use the
architectagent - Pre-merge multi-file review — use
architect-reviewer
Vocabulary discipline
This skill uses precise terms. Do not substitute "component," "service," "API," "boundary," or "layer" — those words drift in meaning across teams and obscure the question being asked.
The full glossary lives in @language.md. The short version:
- Module — anything with an interface and an implementation. Scale-agnostic (function, class, package, slice).
- Interface — everything a caller must know to use the module correctly. Includes signature, invariants, ordering, error modes, perf characteristics. Wider than "API".
- Depth — leverage at the interface. Lots of behaviour per unit of interface a caller must learn = deep. Interface nearly as complex as implementation = shallow.
- Seam — where the interface lives. Distinct from what sits behind it.
- Adapter — a concrete thing that satisfies an interface at a seam.
- Leverage — what callers get from depth.
- Locality — what maintainers get from depth (change concentrates in one place).
What ships with it
2 files 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.
- 1mo ago First seen · 202 lines · 121 tokens per session scan A e056a0bea3b4
module-depth-review is a skill published in the GitHub repository stuartshields/claude-setup (2 stars, last pushed 5mo ago), licensed MIT. It adds 121 tokens to every session and 2,246 once invoked, about $0.0005 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 2026-08-31.
Other skills, from other repositories
code-review
Perform thorough code reviews focusing on unused code, duplications, coding patterns, bugs, and optimizations. Use when user wants code reviewed or audited. Read-only - outputs findings without making changes.
security-audit
Use this skill to perform a security audit, scan for vulnerabilities, check OWASP Top 10 issues, or review code for security problems. Triggered by "security audit", "check security", "find vulnerabilities".
review-pr
Use this skill when the user wants to review a pull request, check a PR for issues, or get feedback on a GitHub PR. Triggered by "review PR", "check PR", "review pull request", or "/review-pr ".
code-remediate
Collect and resolve selected findings in one pass, then verify; bare PR targets use online items, while PR +review adds the latest matching artifact.
code-review
Review local diffs and PRs with specialists and JSON artifacts, or screen an open PR at an evidence gate and advise whether to close it; read-only, never writes to GitHub.
challenge-resolve
Independently review and fix a bounded task through convergence rounds, with evidence-backed closure and explicit stop/remediation decisions. Use only when the user explicitly requests an adversarial review-and-fix loop over an existing implementation, feature, problem, or diff; not for ordinary review (code-review)…