Caveman review
Compress tokens with caveman, a text simplifier that cuts word count while keeping meaning clear
npx -y skills add noman3271/caveman --skill caveman-reviewAssembled 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.
What its author says it does
Copied from the file, not written here
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.
SKILL.md
2.7 KB, 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):
π΄ bug:β broken behavior, will cause incidentπ‘ risk:β works but fragile (race, missing null check, swallowed error)π΅ nit:β style, naming, micro-optim. Author can ignoreβ 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
β "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."
β
L42: π΄ bug: user can be null after .find(). Add guard before .email.
β "It looks like this function is doing a lot of things and might benefit from being broken up into smaller functions for readability."
β
L88-140: π΅ nit: 50-line fn does 4 things. Extract validate/normalize/persist.
β "Have you considered what happens if the API returns a 429? I think we should probably handle that case."
β
L23: π‘ 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.
Gives 0 of the 12 instructions most code review skills give
Counted across 610 of the 674 authors here whose files we hold, read 2026-08-06
- push back with technical reasoning if wrongin 60 of 610, across 24 files
- ask for clarification on unclear itemsin 51 of 610, across 16 files
- fix critical issues immediatelyin 45 of 610, across 29 files
- implement one item at a timein 45 of 610, across 11 files
- group findings by severityin 44 of 610, across 43 files
- verify feedback against the codebasein 42 of 610, across 8 files
- dispatch a code reviewer subagentin 39 of 610, across 23 files
- fix important issues before proceedingin 37 of 610, across 22 files
- test each fix individuallyin 35 of 610, across 7 files
- reply in github comment threadsin 33 of 610, across 5 files
- check for security vulnerabilitiesin 31 of 610, across 27 files
- factualize corrections without over-explainingin 30 of 610, across 2 files
Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once.