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Overengineering review

Skill markoblogo/abvx-agent-skills/skills/overengineering-review

Review code or diffs specifically for needless complexity, replaceable dependencies, dead flexibility, and wrappers over stdlib or native platform behavior. Use when the user asks what can be deleted, simplified, inlined, replaced with stdlib/platform features, or whether a change is over-engineered.From its SKILL.md

Install
npx -y skills add markoblogo/abvx-agent-skills --skill overengineering-review

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

One thing to look at

  • 4 stars4 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

What its file declares

Copied from the file, not written here

The file declares its own license as MIT. That is the author’s claim about this one file, and it is not the same thing as the license GitHub reports for the repository, which is listed with the other numbers below.

SKILL.md

3.1 KB, 602 tokens by cl100k_base, as published. Nobody here has run it

Overengineering Review

Review only for unnecessary complexity. This skill does not hunt general correctness issues unless they directly affect the simplification recommendation.

Pair With

  • Use minimal-diff-builder when the user wants the simplification findings turned into the smallest correct patch.
  • Use complexity-optimizer instead when the real question is performance or algorithmic cost rather than architectural bloat.
  • Use architecture-deepening-review instead when the code is not overbuilt but the boundary design is still wrong.

Review Surface

Look for:

  • needless abstractions;
  • replaceable dependencies;
  • dead flexibility;
  • wrappers around stdlib or native platform features;
  • local helpers or files that only forward to something simpler;
  • speculative extension points with one caller or one implementation.

Findings Taxonomy

Use these tags:

  • delete: code or layer can disappear entirely.
  • stdlib: custom logic should be replaced by a standard-library primitive.
  • native: use built-in platform behavior instead of app code or dependency code.
  • existing-dep: repo already ships a dependency that makes the extra code unnecessary.
  • yagni: speculative abstraction or configurability with no present payoff.
  • shrink: same behavior, fewer moving parts.

Workflow

  1. Determine scope:
    • diff review;
    • file review;
    • broad repo audit.
  2. Ignore style nitpicks that do not reduce real complexity.
  3. Rank findings by payoff:
    • dependency removal;
    • file/layer deletion;
    • abstraction collapse;
    • line-count shrink.
  4. For each finding, capture:
    • location;
    • tag;
    • what is overbuilt;
    • what replaces it;
    • why the simpler path still covers the requirement;
    • any safety caveat.
  5. Keep findings review-grade:
    • specific;
    • actionable;
    • minimal prose;
    • no vague "this feels complex" commentary.

Output Format

One finding per line in ranked order:

<file>:L<line> <tag> <what to cut>. <replacement>. <why it still covers the need>.

End with one compact summary line:

net: -<N> lines, -<M> files, -<K> deps possible.

If nothing meaningful should be cut:

Lean already. Ship.

Boundaries

  • Do not recommend deleting trust-boundary validation, security checks, accessibility basics, or data-loss prevention.
  • Do not turn the review into a broad bug hunt.
  • Do not apply changes unless the user explicitly asks for implementation after review.
  • Treat one focused regression test or self-check as acceptable minimum discipline, not bloat.

Final Report

When a normal prose review is needed, convert the ranked list into:

  • findings ordered by impact;
  • top simplification opportunities;
  • residual caveats where the simpler path only works under current scope.

What ships with it: 2 files

2.4 KB alongside SKILL.md

agents/

Keep looking

Skills are one crate of 326,569. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.