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 tomzx/agents --skill review-codebase-analysisgit clone --depth 1 https://github.com/tomzx/agentsWrote 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/tomzx/agents/review-codebase-analysis)<a href="https://agentmods.dev/skills/tomzx/agents/review-codebase-analysis"><img src="https://agentmods.dev/badge/skills/tomzx/agents/review-codebase-analysis/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/tomzx/agents/review-codebase-analysis"><img src="https://agentmods.dev/badge/skills/tomzx/agents/review-codebase-analysis.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 | $0.00035 | $0.01361 |
| Opus 5.5 | $0.00014 | $0.00544 |
| Sonnet 5.5 | $0.00007 | $0.00272 |
| Haiku 4.5 | $0.00003 | $0.00136 |
Grade A, and why
review-codebase-analysis scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 22d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 123 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Review Codebase Analysis
Audits a codebase analysis and reports findings across five categories: coverage, accuracy, changeability rigor, and impact and migration completeness. The review verifies that the analysis describes the actual code (not assumptions) and that every change disposition is justified and its risk addressed.
Prerequisites
- Apply the shared SDLC conventions in
skills/sdlc/references/shared.md. - If no argument is provided, locate the feature directory under
.sdlc/features/whose frontmatterissuefield references$ISSUE_NUMBER. .sdlc/features/N-<slug>/codebase-analysis.md, or an analysis document provided in context or as a file path.sdlc/features/N-<slug>/requirements.md(optional, improves coverage analysis)
Steps
- Read the analysis from
.sdlc/features/N-<slug>/codebase-analysis.mdif present, otherwise from context or as a file path. - Cross-reference against the requirements document if available: every requirement that implies a code change should map to an analyzed component.
- Spot-check the analysis against the actual codebase to confirm behavior claims and paths.
- Identify issues in each of the categories below.
- Report findings. Omit any category that has no findings.
- Write the findings to
.sdlc/features/N-<slug>/review-codebase-analysis.mdwith frontmatterartifact: codebase-analysis,verdict(approvedif there are no blocking findings,changes-requestedif the author must address findings,rejectedfor a fundamental flaw), andreviewed_at: <ISO date>, and the findings as the body, perskills/sdlc/references/shared.md. Record any unresolved open questions in the findings body. For any question that carries meaningful risk, also invoke/create-assumptionto record it formally. For a chosen change disposition with lasting consequences (e.g. replace vs. extend), invoke/create-decision.
Review Checklist
Coverage
- Does the analysis address every requirement that implies a change to existing code, or are touched components missing?
- Are the search entry points recorded (queries, paths) so the scope is auditable?
- For a greenfield verdict, is the integration boundary (where it attaches to existing systems) actually empty, or was existing code overlooked?
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.
- 22d ago Changed c976eec5023c
- 24d ago Changed 55beded2383a
- 1mo ago First seen · 123 lines · 35 tokens per session scan A 278f138bc147
review-codebase-analysis is a skill published in the GitHub repository tomzx/agents (13 stars, last pushed yesterday), licensed MIT. It adds 35 tokens to every session and 1,361 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 2026-09-03.
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