thermo-nuclear-code-quality-review

thermo-nuclear-code-quality-review is a skill for Claude Code from ayberkcansever/ai-skills. It costs 66 tokens per session (3,062 once invoked), scanned A, original, MIT.

A branch-diff code review covering specification fit, unnecessary complexity, maintainability, merge safety, and feature-document updates.

In plain words
What is it for?
It is for reviewing agent-authored or manually authored branch changes after development and before a pull request, including required documentation synchronization.
Why use it?
It checks several common failure points before a pull request and reports findings before code changes are made.

Skill for Claude Code

Written for Claude Code: disable-model-invocation in frontmatter. Also seen: mentions CLAUDE.md; mentions subagents; mentions AGENTS.md.

Good fit It is for reviewing agent-authored or manually authored branch changes after development and before a pull request, including required documentation synchronization.

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Install with agentmods
npx agentmods add skills/ayberkcansever/ai-skills/thermo-nuclear-code-quality-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 ayberkcansever/ai-skills --skill thermo-nuclear-code-quality-review
Clone the repo
git clone --depth 1 https://github.com/ayberkcansever/ai-skills

Made for: Claude Code.

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 thermo-nuclear-code-quality-review

README.md
[![agentmods](https://agentmods.dev/badge/skills/ayberkcansever/ai-skills/thermo-nuclear-code-quality-review/github.svg)](https://agentmods.dev/skills/ayberkcansever/ai-skills/thermo-nuclear-code-quality-review)
Your own site
<a href="https://agentmods.dev/skills/ayberkcansever/ai-skills/thermo-nuclear-code-quality-review"><img src="https://agentmods.dev/badge/skills/ayberkcansever/ai-skills/thermo-nuclear-code-quality-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 thermo-nuclear-code-quality-review

Your own site · 80×15
<a href="https://agentmods.dev/skills/ayberkcansever/ai-skills/thermo-nuclear-code-quality-review"><img src="https://agentmods.dev/badge/skills/ayberkcansever/ai-skills/thermo-nuclear-code-quality-review.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 66 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,062 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 $0.00066 $0.03062
Opus 5 $0.00033 $0.01531
Sonnet 5 $0.00013 $0.00612
Haiku 4.5 $0.00007 $0.00306

Measured 12d ago against content hash 9c762f074fec, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

thermo-nuclear-code-quality-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.

sdlc/cursor/thermo-nuclear-code-quality-review/SKILL.md · 226 lines

How it starts

The opening of the file, as written. The whole thing — 226 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Thermo-Nuclear Code Quality Review

Review current branch changes through five lenses, in order (the checkout you were launched in — execute-plan launches the reviewer in the ticket worktree). Phases 0–3 are review-first: report findings, change code only if the user says "fix". Phase 4 (docs) is always applied where a feature-docs flow exists.

Maker/checker is unconditional for agent-authored diffs: if any part of the diff was written by an agent in any session (execute-plan or otherwise — resumed agent-authored branches included), run the review as a read-only subagent — the reviewer must not share the implementer's context or be able to edit. Manual invocation on a human-authored diff may run inline. Number every finding N | file:line | severity | problem | fix so accepted findings can be appended to the plan file as structured remediation tasks (see the review loop below).

Pinned review model: the reviewer subagent is launched with a pinned review model — record your chosen slug here (pick the strongest reasoning/thinking model available in your tool) — never inherit the implementer session's model (auto included). If the slug is unavailable, stop and ask the user; never silently substitute. This section is the single source of truth for the slug — write-plan and execute-plan reference it instead of hardcoding it; when the model changes, update it here only.

Persist the verdict: when a plan file exists for the branch, the invoking session (orchestrator) appends the 3-line rollup, the model used, the full-suite command + result, reviewed @ <HEAD SHA> and base @ <base SHA> (both captured in Step 0), and the reviewer subagent link to the plan under a ## Review section (one entry per cycle) — the reviewer subagent is read-only and cannot write the plan; on standalone inline runs the session itself appends. A review that leaves no ## Review entry did not happen — execute-plan's resume check depends on it. A ship verdict is valid only for its recorded HEAD and base SHAs — any later commit invalidates it and requires a new cycle, except commits touching only docs/ paths that leave spec decisions unchanged (doc sync, plan/spec promotion, ## Review entries). A docs commit that edits decisions in spec.md / design.md un-reviews the code; if the base branch moved, re-review before merge.

Step 0 — preconditions, then the diff.

  1. Re-run guard: if the plan's last ## Review entry records Verdict: ship at the current HEAD (or differing from it only by docs-only commits that leave spec decisions unchanged), report "already reviewed at this commit" and stop — re-review only if the user explicitly forces it.
  2. Clean tree required: git status --porcelain must be empty. Staged, unstaged, and untracked changes are invisible to git diff <base>...HEAD and would silently escape review. Dirty tree → stop and report; have the work committed first.
  3. Quirks doc: read the project quirks doc when one exists (e.g. docs/quirks.md — hard-learned domain gotchas) — its entries feed Phase 0's semantic-drift sweep and Phase 3.
  4. Base & anchor: resolve the base (git symbolic-ref refs/remotes/origin/HEAD or main/master), then capture git rev-parse HEAD and git rev-parse <base> — both go into the ## Review entry.
  5. Review git diff <base>...HEAD. Lenses below reconcile cleanly: Phase 0 checks the diff does what was decided; Phase 1 removes what should not exist; Phase 2 restructures what remains.

Start the report with a 3-line rollup:

Verdict: ship | fix-first | block
Top issue: <one line, or "none">
Net: -N lines possible | Lean already

Verdict rules (deterministic):

  • block — any Phase 3 CRITICAL RISK, or a spec decision missing / unapproved drift in Phase 0.
  • fix-first — no blockers, but accepted findings remain open (Phase 0 semantic nits, Phase 1 cuts, Phase 2 structure). Also the cap when a ticket branch has no findable spec/plan (see Phase 0).
  • ship — no open accepted findings AND the full test suite is green at the reviewed SHA, evidenced by the suite command + result recorded in the ## Review entry (the orchestrator re-runs it after the last fix; a targeted gate command alone does not qualify). No recorded evidence → cap at fix-first.

Read the full file on GitHub · 226 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 · 226 lines · 66 tokens per session scan A 9c762f074fec

Subscribe to this mod's changes

thermo-nuclear-code-quality-review is a skill published in the GitHub repository ayberkcansever/ai-skills (2 stars, last pushed 8d ago), licensed MIT. It adds 66 tokens to every session and 3,062 once invoked, about $0.0003 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.