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Caveman review

Skill dills122/ai-central/templates/skills/imported/caveman/skills/caveman-review

Ultra-compressed code review comments. Cuts noise from PR feedback while preserving the actionable signal. Each comment is one line: location, problem, fix. Use when user says "review this PR", "code review", "review the diff", "/review", or invokes /caveman-review. Auto-triggers when reviewing pull requests.From its SKILL.md

Install
npx -y skills add dills122/ai-central --skill caveman-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

  • 0 stars0 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.

SKILL.md

2.7 KB, 593 tokens by cl100k_base, as published. Nobody here has run it

Write code review comments terse and actionable. One line per finding. Location, problem, fix. No throat-clearing.

Rules

Format: L<line>: <problem>. <fix>. β€” or <file>:L<line>: ... when reviewing multi-file diffs.

Severity prefix (optional, when mixed):

  • πŸ”΄ bug: β€” broken behavior, will cause incident
  • 🟑 risk: β€” works but fragile (race, missing null check, swallowed error)
  • πŸ”΅ nit: β€” style, naming, micro-optim. Author can ignore
  • ❓ q: β€” genuine question, not a suggestion

Drop:

  • "I noticed that...", "It seems like...", "You might want to consider..."
  • "This is just a suggestion but..." β€” use nit: instead
  • "Great work!", "Looks good overall but..." β€” say it once at the top, not per comment
  • Restating what the line does β€” the reviewer can read the diff
  • Hedging ("perhaps", "maybe", "I think") β€” if unsure use q:

Keep:

  • Exact line numbers
  • Exact symbol/function/variable names in backticks
  • Concrete fix, not "consider refactoring this"
  • The why if the fix isn't obvious from the problem statement

Examples

❌ "I noticed that on line 42 you're not checking if the user object is null before accessing the email property. This could potentially cause a crash if the user is not found in the database. You might want to add a null check here."

βœ… L42: πŸ”΄ bug: user can be null after .find(). Add guard before .email.

❌ "It looks like this function is doing a lot of things and might benefit from being broken up into smaller functions for readability."

βœ… L88-140: πŸ”΅ nit: 50-line fn does 4 things. Extract validate/normalize/persist.

❌ "Have you considered what happens if the API returns a 429? I think we should probably handle that case."

βœ… L23: 🟑 risk: no retry on 429. Wrap in withBackoff(3).

Auto-Clarity

Drop terse mode for: security findings (CVE-class bugs need full explanation + reference), architectural disagreements (need rationale, not just a one-liner), and onboarding contexts where the author is new and needs the "why". In those cases write a normal paragraph, then resume terse for the rest.

Boundaries

Reviews only β€” does not write the code fix, does not approve/request-changes, does not run linters. Output the comment(s) ready to paste into the PR. "stop caveman-review" or "normal mode": revert to verbose review style.

What ships with it: 1 file

1.2 KB alongside SKILL.md

Gives 0 of the 12 instructions most code review skills give in 593 tokens

Counted across 668 of the 814 authors here whose files we hold, read 2026-09-06

  • Provide technical reasoning when pushing backin 84 of 668, across 70 files
  • Fix critical issues immediatelyin 77 of 668, across 60 files
  • Dispatch a code reviewer subagentin 76 of 668, across 59 files
  • Fix important issues before proceedingin 73 of 668, across 56 files
  • Ask for clarification on unclear itemsin 68 of 668, across 56 files
  • Verify feedback against codebase before implementationin 66 of 668, across 55 files
  • Implement fixes one at a timein 64 of 668, across 53 files
  • Test each fix individuallyin 62 of 668, across 51 files
  • Restate technical requirements in own wordsin 57 of 668, across 46 files
  • Reply to inline comments in the specific threadin 51 of 668, across 40 files
  • Note minor issues for laterin 49 of 668, across 34 files
  • Group findings by severityin 48 of 668, across 47 files

Said here and by no other author read

  • Write comments in one line
  • Use full explanation for security findings
  • Use full explanation for architectural disagreements
  • Use full explanation for onboarding contexts

Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once. Length counted with cl100k_base; the agent that loads this file may tokenize it differently.

Keep looking

Skills are one crate of 325,949. 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.