final-review

final-review is a skill for Claude Code from karsten-s-nielsen/mad-scientist-skills. It costs 80 tokens per session (3,072 once invoked), scanned A, original, MIT.

A pre-commit quality check for code and documentation. It reviews consistency, completeness, project conventions, and architecture diagrams before changes are committed.

In plain words
What is it for?
Use it before committing or pushing changes, after a feature or major refactor, or when you need a broad project review.
Why use it?
It catches unfinished work, documentation drift, and mismatches between the code and its described architecture.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin. Also seen: mentions CLAUDE.md; mentions AGENTS.md.

Part of the mad-scientist-skills plugin — 10 skills, 4 commands shipped together

Good fit Use it before committing or pushing changes, after a feature or major refactor, or when you need a broad project review.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/karsten-s-nielsen/mad-scientist-skills/final-review
Install

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.

Any agent
npx skills add karsten-s-nielsen/mad-scientist-skills --skill final-review
Clone the repo
git clone --depth 1 https://github.com/karsten-s-nielsen/mad-scientist-skills

Made for: Claude Code.

Or install mad-scientist-skills, the plugin that ships this one along with the rest of its 10 skills, 4 commands.

Wrote 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.

agentmods badge for final-review

README.md
[![agentmods](https://agentmods.dev/badge/skills/karsten-s-nielsen/mad-scientist-skills/final-review/github.svg)](https://agentmods.dev/skills/karsten-s-nielsen/mad-scientist-skills/final-review)
Your own site
<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.

agentmods 80×15 button for final-review

Your own site · 80×15
<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>
Per session 80 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,072 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce 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

Measured 12d ago against content hash 8ca8848716ef, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

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.

plugins/mad-scientist-skills/skills/final-review/SKILL.md · 197 lines

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, any usage, 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 scanning
  • observability-audit — logging, metrics, tracing, alerting, SLI/SLO coverage
  • optimization-audit — algorithm efficiency, database queries, caching, concurrency, cloud cost
  • cognitive-interface-audit — usability, mental model alignment, cognitive load, accessibility (if UI exists)
  • documentation-audit — linguistic precision, structural taxonomy, audience calibration, completeness

Read the full file on GitHub · 197 lines

Changes

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.

  1. 12d ago First seen · 197 lines · 80 tokens per session scan A 8ca8848716ef

Subscribe to this mod's changes

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.

Related

Other skills, from other repositories

audit

This skill should be used when the user asks to "audit spec coverage", "find uncovered modules", "scan for missing specs", "check wyx coverage", "get spec TODO list", "wyx audit", "wyx", or wants a prioritized list of wyx skill commands for uncovered modules. Scans for coverage gaps, pipeline/sync candidates, and…

jlifyio/wyx · 81 tokens

refactor

Automated iterative code refactoring with swarm-orchestrated specialist agents including deep codebase discovery, confidence-scored code review, and security analysis. Use this skill when the user wants to improve existing code quality, clean up messy code, restructure, simplify, reduce tech debt, or perform…

zircote-plugins/refactor · 112 tokens

recipe-front-review

Reviews completed frontend implementation for governing-source compliance, scope economy, repository quality, and security, then applies user-approved React corrections.

shinpr/claude-code-workflows · 29 tokens

new-skill

Scaffold a new brooks-lint analysis skill so it passes npm run validate and npm run evals on the first try — generates skills/{name}/SKILL.md (with the mandatory "Do NOT trigger for:" clause and a Process section citing guide step ranges) plus skills/{name}/{name}-guide.md (sequentially numbered steps), then appends…

hyhmrright/brooks-lint · 145 tokens

release

Cut a brooks-lint release: set the version in package.json, propagate it across all four plugin manifests and every version-bearing text file (README badges, docs site metadata), write the CHANGELOG entry, validate, then commit, push, tag, and publish the GitHub release. Triggers when the maintainer asks to "release"…

hyhmrright/brooks-lint · 135 tokens

brooks-audit

Architecture audit that maps module dependencies, checks layering integrity, and flags structural decay across a codebase, drawing on twelve classic engineering books. Triggers when: user asks to audit architecture, review folder/module structure, check for circular imports, understand how the codebase is organized…

hyhmrright/brooks-lint · 143 tokens