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 karsten-s-nielsen/mad-scientist-skills --skill final-reviewgit clone --depth 1 https://github.com/karsten-s-nielsen/mad-scientist-skillsWrote 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/karsten-s-nielsen/mad-scientist-skills/final-review)<a href="https://agentmods.dev/skills/karsten-s-nielsen/mad-scientist-skills/final-review"><img src="https://agentmods.dev/badge/skills/karsten-s-nielsen/mad-scientist-skills/final-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/karsten-s-nielsen/mad-scientist-skills/final-review"><img src="https://agentmods.dev/badge/skills/karsten-s-nielsen/mad-scientist-skills/final-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 | $0.00080 | $0.03072 |
| Opus 5 | $0.00040 | $0.01536 |
| Sonnet 5 | $0.00016 | $0.00614 |
| Haiku 4.5 | $0.00008 | $0.00307 |
Grade A, and why
final-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 12d 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 — 197 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Final Review
A comprehensive pre-commit quality gate that ensures code, documentation, and architecture diagrams are consistent, complete, and follow professional standards.
When to use this skill
- Before committing or pushing changes
- After completing a feature or significant refactor
- When the user says "final review", "check everything", "make sure it's all up to date", or "review before commit"
- Periodically to catch documentation drift
Review process
Execute all phases in order. Do NOT skip phases. Do NOT claim completion without evidence.
Phase 1: Codebase Discovery
Explore the project to understand its current state:
- Read the project's
CLAUDE.md,AGENTS.md,README.md, and any other root-level documentation - Identify the tech stack, project structure, and architectural patterns
- Note the testing framework and how tests are run
- Identify all configuration files (
package.json,pyproject.toml,tsconfig.json, etc.)
Phase 2: Code Quality Review
Review all source code as a professional software architect:
- Consistency: Naming conventions, file organization, import patterns, error handling patterns
- Best practices: SOLID principles, DRY, proper error handling, security (OWASP top 10)
- Dead code: Unused imports, unreachable code, commented-out blocks, orphaned files
- Type safety: Missing types,
anyusage, incomplete interfaces - Dependencies: Unused dependencies, outdated versions with known vulnerabilities
- Tests: Coverage gaps, missing edge cases, outdated test assertions
For deeper analysis, run the specialized audit skills from this plugin:
security-audit— STRIDE threat modeling, infrastructure hardening, supply chain audit, secrets scanningobservability-audit— logging, metrics, tracing, alerting, SLI/SLO coverageoptimization-audit— algorithm efficiency, database queries, caching, concurrency, cloud costcognitive-interface-audit— usability, mental model alignment, cognitive load, accessibility (if UI exists)documentation-audit— linguistic precision, structural taxonomy, audience calibration, completeness
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.
- 12d ago First seen · 197 lines · 80 tokens per session scan A 8ca8848716ef
final-review is a skill published in the GitHub repository karsten-s-nielsen/mad-scientist-skills (3 stars, last pushed 13d ago), licensed MIT. It adds 80 tokens to every session and 3,072 once invoked, about $0.0004 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 2026-08-31.
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