audit-memory
Audit Claude's saved memories for claims that no longer hold true — verify each against current code, PRs and tickets, then…
Run an extremely strict structural and architectural quality review on a diff, branch, or file set, hunting for "code judo" moves that dramatically simplify the implementation — not correctness bugs or style nits.
$ npx -y skills add intercom/2x-skills --skill thermo-nuclear-code-review --agent claude-codeHow it fires
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Run an extremely strict structural and architectural quality review on a diff, branch, or file set, hunting for "code judo" moves that dramatically simplify the implementation — not correctness bugs or style nits.
name: thermo-nuclear-code-review description: > Run an extremely strict structural and architectural quality review on a diff, branch, or file set, hunting for "code judo" moves that dramatically simplify the implementation — not correctness bugs or style nits. metadata: user-invocable: true argument-hint: "[PR URL, branch, or file paths]" keywords: [thermonuclear, code judo, maintainability audit, harsh review, deep code review] allowed-tools: Bash, Read, Glob, Grep
An unusually strict review focused on structural quality, architectural health, abstraction cleanliness, and codebase maintainability. This is not a correctness review — it asks whether the code is making the codebase *better* or *worse*.
The guiding principle is **code judo**: actively search for restructurings that preserve behavior while making the implementation dramatically simpler, smaller, more direct, and more elegant. Do not stop at "this could be a bit cleaner." Look for moves where whole branches, helpers, modes, conditionals, or layers disappear entirely. Prefer the solution that feels inevitable in hindsight.
| This review covers | This review does NOT cover | |---|---| | Structural quality and architectural health | Correctness bugs (use a dedicated correctness-focused review) | | Abstraction quality and decomposition | Style nits and formatting | | Complexity growth and spaghetti detection | Test coverage gaps | | Layer violations and architectural drift | Security vulnerabilities | | File size and modularity | Performance micro-optimizations | | Type boundary and contract cleanliness | Linting violations |
If a correctness review or repo-specific rule enforcement is needed, run that separately. This skill is the architectural conscience.
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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. Assume there is often a code judo move available — a reorganization that uses the existing architecture more effectively and makes the change dramatically simpler. If you see a path to delete complexity rather than rearrange it, push hard for that path.
Treat crossing 1000 lines as a structural smell. Prefer extracting helpers, subcomponents, modules, or local abstractions instead of letting a file sprawl. If the diff crosses that threshold, explicitly call it out. Only waive this if the file is clearly organized and the growth is structurally justified — not just "I added more methods here because this is where the other ones are."
Be highly suspicious of new ad-hoc conditionals, scattered special cases, or one-off branches inserted into unrelated flows. If a change adds if-statements in unrelated code paths, 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.
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.
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.
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