thermo-nuclear-code-quality-review
Runs an extremely strict maintainability review for abstraction quality, giant files, and spaghetti-condition growth.
Skill by Tonours
Install
Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.
npx agentmarket install skill/tonours-thermo-nuclear-code-quality-review
Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.
Get the weekly diff
The weekly diff: one email a week with new agent tools, notable updates and grade changes, plus security alerts for tools you follow. Double opt-in, one-click unsubscribe.
About
Use cases: security, marketing
Reviews
Write a reviewNo reviews yet. Installed it? Reviews come from verified installers only. How reviews work
Permissions
What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.
- Tools
- No tools found
- Secrets
- None asked for
- Install scripts
- None found
Network hosts it talks to 1
codeload.github.com· found in install command
Files it touches
~/.claude/skills/thermo-nuclear-code-quality-review
What's inside
- Skill name
thermo-nuclear-code-quality-review- Description
- Runs an extremely strict maintainability review for abstraction quality, giant files, and spaghetti-condition growth. Use for a thermo-nuclear code quality review, thermonuclear review, deep code quality audit, or especially harsh maintainability review; not for quick reviews or for approving borderline code.
- License
- MIT
- Instructions
- 188 lines in SKILL.md · view on GitHub
Files (1)
- SKILL.md
SKILL.md (first lines)
# Thermo-Nuclear Code Quality Review Use this skill for an unusually strict review focused on implementation quality, maintainability, abstraction quality, and codebase health. Above all, this skill should push the reviewer to be **ambitious** about code structure. Do not merely identify local cleanup opportunities. Actively search for "code judo" moves: restructurings that preserve behavior while making the implementation dramatically simpler, smaller, more direct, and more elegant. ## Core Prompt Start from this baseline: > Perform a deep code quality audit of the current branch's changes. > Rethink how to structure / implement the changes to meaningfully improve code quality without impacting behavior. > Work to improve abstractions, modularity, reduce Spaghetti code, improve succinctness and legibility. > Be ambitious, if there is a clear path to improving the implementation that involves restructuring some of the codebase, go for it. > Be extremely thorough and rigorous. Measure twice, cut once. ## Non-Negotiable Additional Standards Apply the baseline prompt above, plus these explicit review rules: 0. **Be ambitious about structural simplification.** - Do not stop at "this could be a bit cleaner." - Look for opportunities to reframe the change so that whole branches, helpers, modes, conditionals, or layers disappear entirely. - Prefer the solution that makes the code feel inevitable in hindsight. - Assume there is often a "code judo" move available: a re-organization that uses the existing architecture more effectively and makes the change dramatically simpler and more elegant. - If you see a path to delete complexity rather than rearrange it, push hard for that path. 1. **Do not let a PR push a file from under 1k lines to over 1k lines without a very strong reason.** - Treat this as a strong code-quality smell by default. - Prefer extracting helpers, subcomponents, modules, or local abstractions instead of letting a file sprawl past 1000 lines. - If the diff crosses that threshold, explicitly ask whether the code should be decomposed first. - Only waive this if there is a compelling structural reason and the resulting file is still clearly organized. 2. **Do not allow random spaghetti growth in existing code.** - Be highly suspicious of new ad-hoc conditionals, scattered special cases, or one-off branches inserted into unrelated flows. - If a change adds "weird if statements in random places", treat that as a design problem, not a stylistic nit. - Prefer pushing the logic into a dedicated abstraction, helper, state machine, policy object, or separate module instead of tangling an existing path. - Call out changes that make the surrounding code harder to reason about, even if they technically work. 3. **Bias toward cleaning the design, not just accepting working code.** - If behavior can stay the same while the structure becomes meaningfully cleaner, push for the cleaner version. - Do not rubber-stamp "it works" implementations that leave the codebase messier. - Strongly prefer simplifications that remove moving pieces altogether over refactors that merely spread the same complexity around. 4. **Prefer direct, boring, maintainable code over hacky or magical code.** - Treat brittle, ad-hoc, or "magic" behavior as a code-quality problem. - Be skeptical of generic mechanisms that hide simple data-shape assumptions. - Flag thin abstractions, identity wrappers, or pass-through helpers that add indirection without buying clarity. 5. **Push hard on type and boundary cleanliness when they affect maintainability.** - Question unnecessary optionality, `unknown`, `any`, or cast-heavy code when a clearer type boundary could exist. - Prefer explicit typed models or shared contracts over loosely-shaped ad-hoc objects. - If a branch relies on silent fallback to paper over an unclear invariant, ask whether the boundary should be made explicit instead. 6. **Keep logic in the canonical layer and reuse existing helpers.** - Call out feature logic leaking into shared paths or implementation details leaking through APIs. - Prefer existing canonical utilities/helpers over bespoke one-offs. - Push code toward the right package, service, or module instead of normalizing architectural drift. 7. **Treat unnecessary sequential orchestration and non-atomic updates as design smells when the cleaner structure is obvious.** - If independent work is serialized for no good reason, ask whether the flow should run in parallel instead. - If related updates can leave state half-applied, push for a more atomic structure. - Do not over-index on micro-optimizations, but do flag avoidable orchestration complexity that makes the implementation more brittle. ## Primary Review Questions For every meaningful change, ask: - Is there a "code judo" move that would make this dramatically simpler? - Can this change be reframed so fewer concepts, branches, or helper layers are needed? - Does this improve or worsen the local architecture? - Did the diff add branching complexity where a better abstraction should exist? - Did a previously cohesive module become more coupled, more stateful, or harder to scan? - Is this logic living in the right file and layer? - Did this change enlarge a file or component past a healthy size boundary? - Are there repeated conditionals that signal a missing model or missing helper? - Is the implementation direct and legible, or does it rely on special cases and incidental control flow? - Is this abstraction actually earning its keep, or is it just a wrapper? - Did the diff introduce casts, optionality, or ad-hoc object shapes that obscure the real invariant? - Is this logic living in the canonical layer, or did the diff leak details across a boundary? - Is this orchestration more sequential or less atomic than it needs to be? ## What to Flag Aggressively Escalate findings when you see: - A complicated implementation where a cleaner reframing could delete whole categories of complexity. - Refactors that move code around but fail to reduce the number of concepts a reader must hold in their head. - A file crossing 1000 lines due to the PR, especially if the new code could be split out. - New conditionals bolted onto unrelated code paths. - One-off booleans, nullable modes, or flags that complicate existing control flow. - Feature-specific logic leaking into general-purpose modules. - Generic "magic" handling that hides simple structure and makes the code harder to reason about. - Thin wrappers or identity abstractions that add indirection without simplifying anything. - Unnecessary casts, `any`, `unknown`, or optional params that muddy the real contract. - Copy-pasted logic instead of extracted helpers. - Narrow edge-case handling implemented in the middle of an already busy function. - Refactors that technically pass tests but make the code less modular or less readable. - "Temporary" branching that is likely to become permanent debt. - Bespoke helpers where the codebase already has a canonical utility for the job. - Logic added in the wrong layer/package when it should live somewhere more central. - Sequential async flow where obviously independent work could stay simpler and clearer with parallel execution. - Partial-update logic that leaves state less atomic than necessary. ## Preferred Remedies When you identify a code-quality problem, prefer suggestions like: - Delete a whole layer of indirection rather than polishing it. - Reframe the state model so conditionals disappear instead of getting centralized. - Change the ownership boundary so the feature becomes a natural extension of an existing abstraction. - Turn special-case logic into a simpler default flow with fewer exceptions. - Extract a helper or pure function. - Split a large file into smaller focused modules. - Move feature-specific logic behind a dedicated abstraction. - Replace condition chains with a typed model or explicit dispatcher. - Separate orchestration from business logic. - Collapse duplicate branches into a single clearer flow. - Delete wrappers that do not meaningfully clarify the API.
From Tonours/etabli, MIT.
More from Tonours/etabli
- 0.570score
react-doctor-100
Tonours
Runs react-doctor on React codebases and iteratively fixes diagnosed issues until the project reaches a verified score of 100 without shortcuts.
SkillAFreshness: AClaude Code +9 - 0.570score
adr
Tonours
Records a lightweight Architecture Decision Record for a decision made in this session.
SkillAFreshness: AClaude Code +9 - 0.567score
employer-docs-writing
Tonours
Writes or rewrites pages for the employer Mintlify documentation (~/work/docs) in the corpus voice.
SkillAFreshness: AClaude Code +9 - 0.561score
write-direct
Tonours
Writes or rewrites internal docs and messages in Anthony's direct, informal voice (French by default).
SkillAFreshness: AClaude Code +9 - 0.561score
spec
Tonours
Writes or revises employer specs, technical Epics and design docs from the bundled templates.
SkillAFreshness: AClaude Code +9 - 0.561score
coolify
Tonours
Manages Coolify Cloud via its official CLI (servers, apps, databases, deployments, logs, env, backups).
SkillAFreshness: AClaude Code +9 - 0.561score
code-quality
Tonours
Runs the bounded convention and stack-quality pass on a diff.
SkillAFreshness: AClaude Code +9 - 0.560score
adversary
Tonours
Red-teams a PLAN.md, diff or design as a hostile challenger.
SkillAFreshness: AClaude Code +9 - 0.560score
implement
Tonours
Implements an existing READY PLAN.md without replanning.
SkillAFreshness: AClaude Code +9 - 0.560score
pr-council-review
Tonours
Runs a three-pass review of one PR (code-review + thermo-nuclear, then forest:validator as the council), dry-run by default.
SkillAFreshness: AClaude Code +9 - 0.557score
plan-implement
Tonours
Plans, then implements the same task in one run once PLAN.md is READY.
SkillAFreshness: AClaude Code +9 - 0.556score
employer-backend-suite
Tonours
Routes employer server, agent-nodejs, BFF, MCP, OAuth/JWT, permissions v4, workflow execution and Zendesk work to existing KB notes.
SkillAFreshness: AClaude Code +9
Signals
- Stars
- 0
- Forks
- 0
- Open issues
- 0
- Last commit (this folder)
- Oct 23, 2026 (5 days ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- MIT
- Repository
- github.com/Tonours/etabli
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
More from Tonours
- 0.570score
react-doctor-100
Tonours
Runs react-doctor on React codebases and iteratively fixes diagnosed issues until the project reaches a verified score of 100 without shortcuts.
SkillAFreshness: AClaude Code +9 - 0.570score
adr
Tonours
Records a lightweight Architecture Decision Record for a decision made in this session.
SkillAFreshness: AClaude Code +9 - 0.567score
employer-docs-writing
Tonours
Writes or rewrites pages for the employer Mintlify documentation (~/work/docs) in the corpus voice.
SkillAFreshness: AClaude Code +9 - 0.561score
coolify
Tonours
Manages Coolify Cloud via its official CLI (servers, apps, databases, deployments, logs, env, backups).
SkillAFreshness: AClaude Code +9 - 0.561score
spec
Tonours
Writes or revises employer specs, technical Epics and design docs from the bundled templates.
SkillAFreshness: AClaude Code +9 - 0.561score
code-quality
Tonours
Runs the bounded convention and stack-quality pass on a diff.
SkillAFreshness: AClaude Code +9
Cite this page
thermo-nuclear-code-quality-review skill. Agent Mart. https://agentmart.dev/skills/tonours-thermo-nuclear-code-quality-review (last updated 2026-10-24)