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 agentmods add skills/penwyp/claudepreference/doc-code-review-reportnpx skills add penwyp/ClaudePreference --skill doc-code-review-reportgit clone --depth 1 https://github.com/penwyp/ClaudePreferenceWrote 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/penwyp/claudepreference/doc-code-review-report)<a href="https://agentmods.dev/skills/penwyp/claudepreference/doc-code-review-report"><img src="https://agentmods.dev/badge/skills/penwyp/claudepreference/doc-code-review-report.svg" alt="Measured on agentmods" 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 | $0.00091 | $0.01174 |
| Opus 5 | $0.00046 | $0.00587 |
| Sonnet 5 | $0.00018 | $0.00235 |
| Haiku 4.5 | $0.00009 | $0.00117 |
Grade A, and why
doc-code-review-report 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 4d 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 — 107 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Doc Code Review Report
Overview
Review the user's text or document as a claim source, then verify those claims against the real codebase. Produce an evidence-backed review report, not a summary, and separate confirmed issues from inference.
Read references/report-template.md only when you need a ready-made report scaffold.
Workflow
- Normalize the review input.
- Accept plain text, Markdown, notes, PR descriptions, API docs, or design documents.
- Extract concrete claims: intended behavior, request flow, data fields, state changes, error handling, and unfinished work markers.
- If the input is broad, narrow it to the specific flow, module, or interface under review.
- Locate the implementation before judging it.
- Find the real entry points first: routes, pages, handlers, services, schedulers, workers, repositories, generated clients, OpenAPI specs, or protocol types.
- Prefer concrete call paths over keyword-level guesses.
- If the document describes a frontend flow, trace both UI state transitions and backend requests.
- Verify behavior claim by claim.
- Check whether the implemented logic matches the stated requirement or document claim.
- Distinguish:
- documented but not implemented
- implemented but undocumented
- implemented differently from the document
- behavior cannot be confirmed from current code
- Review for correctness and bug risk.
- Look for broken conditions, missing branches, invalid assumptions, stale state, race windows, missing null or empty handling, unchecked errors, and inconsistent data transformations.
- Treat "works on happy path only" as a real finding when failure branches are absent or contradicted by the input document.
- Cross-check frontend and backend contracts when the flow crosses layers.
- Confirm method, path, path params, query params, body fields, enum values, response fields, and error shapes.
- Compare frontend request builders, generated API clients, backend handlers, service DTOs, protocol definitions, and local OpenAPI or schema files.
- Flag mismatches such as renamed fields, optional-vs-required drift, type drift, enum drift, and response shape assumptions unsupported by backend code.
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.
- 4d ago First seen · 107 lines · 91 tokens per session scan A fdb2d1686879
doc-code-review-report is a skill published in the GitHub repository penwyp/ClaudePreference (137 stars, last pushed 3mo ago), licensed MIT. It adds 91 tokens to every session and 1,174 once invoked, about $0.0005 per session on Opus 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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