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技能库 智客分类:Agent 工作流 thermo-nuclear-code-quality-review

Thermo Nuclear Code Quality Review

进行极严格的可维护性审查 抽象质量,巨型文件, 和意大利面-条件增长。 用于热核码质量审查,热核审查,深码质量审计,或特别严苛的可维护性审查.

24367 安装量

官方网址:skills.sh

技能介绍

先看中文介绍;官方 description 原文单独保留,不改写 SKILL.md。

做什么

进行极严格的可维护性审查 抽象质量,巨型文件, 和意大利面-条件增长。 用于热核码质量审查,热核审查,深码质量审计,或特别严苛的可维护性审查.

何时用

官方 description 未单独写出 Use when。按规范,代理会在用户任务与这段 description 的关键词匹配时激活本技能。

代理如何加载

按 Agent Skills 渐进披露:启动时只加载 name 与 description(约 100 token);任务匹配后才读入整份 SKILL.md 正文;scripts/、references/、assets/ 仅在需要时再读。 本文件正文结构:Thermo-Nuclear Code Quality Review、Core Prompt、Non-Negotiable Additional Standards、Primary Review Questions、What to Flag Aggressively、Preferred Remedies。

文件分析

文件分析:这是一份仅含 SKILL.md 的指令型技能,代理激活后整份正文进入上下文。

官方 description(原文)

Run 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.

Thermo-Nuclear Code Quality ReviewCore PromptNon-Negotiable Additional StandardsPrimary Review QuestionsWhat to Flag AggressivelyPreferred RemediesReview ToneOutput ExpectationsApproval Bar

来源分类:skills.sh agent-skill

SKILL.md 与 Agent 调用

官方规范 ↗
name
thermo-nuclear-code-quality-review
description
Run 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.
  1. 发现技能客户端向 Agent 提供名称与描述目录。
  2. 匹配与调用用户指定或任务匹配后,载入 SKILL.md 指令。
  3. 按需加载按步骤读取参考文档、使用脚本与素材。

具体调用语法与可用工具以目标 Agent 客户端为准。 查看调用机制说明 ↗

安装这个技能

Skills CLI ↗

先选择目标 Agent 和安装范围,保留技能包的附属文件,安装后检查客户端能否发现该技能。

交给 Agent 安装

复制安装指令给支持 Agent Skills 的代理,确认其中的目标目录与客户端匹配。

把 Agent Skill「thermo-nuclear-code-quality-review」安装到我的项目:SKILL.md 原文与官方 description 见 https://zicq.com/zh/skills/skl-eb3534c99e154acc-Thermo-Nuclear-Code-Quality-Review.html
请存为 .cursor/skills/thermo-nuclear-code-quality-review/SKILL.md 或 .claude/skills/thermo-nuclear-code-quality-review/SKILL.md,frontmatter 的 name 与 description 保持原样,不要改写。

GitHub 完整包 ↗

终端安装 · Skills CLI

需要 Node.js 与 npx。先查看仓库技能列表,确认实际名称。

npx skills add 'https://github.com/cursor/plugins' --list

npx skills add 'https://github.com/cursor/plugins' --skill 'thermo-nuclear-code-quality-review'

CLI 会交互选择目标 Agent,默认安装到项目;用户级安装使用 -g。先通过查看命令核对仓库内容,再用 npx skills list 检查已安装技能。

阅读排版

name: thermo-nuclear-code-quality-review description: Run 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. disable-model-invocation: true

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:

  1. 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.
  2. 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.
  3. 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.
  4. 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.
  5. 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.
  6. 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.
  7. 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.
  8. 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.
  • Reuse the existing canonical helper instead of introducing a near-duplicate.
  • Make type boundaries more explicit so the control flow gets simpler.
  • Move the logic to the package/module/layer that already owns the concept.
  • Parallelize independent work when that also simplifies the orchestration.
  • Restructure related updates into a more atomic flow when partial state would be harder to reason about.

Do not be satisfied with "maybe rename this" feedback when the real issue is structural. Do not be satisfied with a merely cleaner version of the same messy idea if there is a plausible path to a much simpler idea.

Review Tone

Be direct, serious, and demanding about quality. Do not be rude, but do not soften major maintainability issues into mild suggestions. If the code is making the codebase messier, say so clearly. If the implementation missed an opportunity for a dramatic simplification, say that clearly too.

Good phrases:

  • this pushes the file past 1k lines. can we decompose this first?
  • this adds another special-case branch into an already busy flow. can we move this behind its own abstraction?
  • this works, but it makes the surrounding code more spaghetti. let's keep the behavior and restructure the implementation.
  • this feels like feature logic leaking into a shared path. can we isolate it?
  • this abstraction seems unnecessary. can we just keep the direct flow?
  • why does this need a cast / optional here? can we make the boundary more explicit instead?
  • this looks like a bespoke helper for something we already have elsewhere. can we reuse the canonical one?
  • i think there's a code-judo move here that makes this much simpler. can we reframe this so these branches disappear?
  • this refactor moves complexity around, but doesn't really delete it. is there a way to make the model itself simpler?

Output Expectations

Prioritize findings in this order:

  1. Structural code-quality regressions
  2. Missed opportunities for dramatic simplification / code-judo restructuring
  3. Spaghetti / branching complexity increases
  4. Boundary / abstraction / type-contract problems that make the code harder to reason about
  5. File-size and decomposition concerns
  6. Modularity and abstraction issues
  7. Legibility and maintainability concerns

Do not flood the review with low-value nits if there are larger structural issues. Prefer a smaller number of high-conviction comments over a long list of cosmetic notes.

Approval Bar

Do not approve merely because behavior seems correct. The bar for approval is:

  • no clear structural regression
  • no obvious missed opportunity to make the implementation dramatically simpler when such a path is visible
  • no unjustified file-size explosion
  • no obvious spaghetti-growth from special-case branching
  • no obviously hacky or magical abstraction that makes the code harder to reason about
  • no unnecessary wrapper/cast/optionality churn obscuring the real design
  • no clear architecture-boundary leak or avoidable canonical-helper duplication
  • no missed opportunity for an obvious decomposition that would materially improve maintainability

Treat these as presumptive blockers unless the author can justify them clearly:

  • the PR preserves a lot of incidental complexity when there is a plausible code-judo move that would delete it
  • the PR pushes a file from below 1000 lines to above 1000 lines
  • the PR adds ad-hoc branching that makes an existing flow more tangled
  • the PR solves a local problem by scattering feature checks across shared code
  • the PR adds an unnecessary abstraction, wrapper, or cast-heavy contract that makes the design more indirect
  • the PR duplicates an existing helper or puts logic in the wrong layer when there is a clear canonical home

If those conditions are not met, leave explicit, actionable feedback and push for a cleaner decomposition.

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