performance-review
Skill8 starsChanged 6 months agoMITView on GitHub
Review code changes for performance anti-patterns — N+1 queries, unbounded results, blocking ops.
26 other projects use a version of this.
Adopted by
Most recently taken up by
- Smaui94/ClaudeSkillCollectiontheir own version, first seen Nov 8, 2026
- nisarth/claude-skills-storetheir own version, first seen Nov 8, 2026
- frnkgns/Overgeared-Skillstheir own version, first seen Nov 8, 2026
- flopperj/dotfiles-coretheir own version, first seen Nov 4, 2026
- Cure-Consulting-Group/ProductEngineeringSkillstheir own version, first seen Nov 4, 2026
- nledford/engineering-review-boardtheir own version, first seen Nov 3, 2026
Used with
Projects with it also use ci-cd-pipeline, architecture-review and 2 more.
Other files people use alongside this one.
Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
nanvixSkillci-cd-pipeline
Guide for Nanvix CI and GitHub Actions workflow behavior, including local pipeline execution and matrix coverage. Use this when asked about CI checks, workflow failures, or release flow.
Also in 3 projects that use this
SentrySkillarchitecture-review
Staff-level codebase health review. Finds monolithic modules, silent failures, type safety gaps, test coverage holes, and LLM-friendliness issues.
Also in 7 projects that use this
MicrosoftSkillapi-design
Guide for designing and documenting RESTful APIs. Use when asked to design an API, create endpoints, or document an API.
Also in 3 projects that use this
OpenAISkillsystematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes
Also in 3 projects that use this
Other versions26 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 26
- anthropics/knowledge-work-plugins★ 35ksame name
- genspark-ai/genoffice★ 12ksame name
- microsoft/intelligent-terminal★ 2.2ksame name
- borgbase/vykar★ 722same name
- ShipSecAI/studio★ 380same name
- nledford/engineering-review-board★ 11same name
- frnkgns/Overgeared-Skills★ 7same name
- Sagargupta16/agent-recipes★ 4same name
- vikisingh23/neuraforge-ai★ 4same name
- aiimpactagency/social-media-team★ 3same name
16 more not listed
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository16 other files it gives its agents.
- .claude/rules/common/agents.mdAGENTS.md
- agent-creatorSkill
- architect-reviewSkill
- build-fixSkill
- code-reviewSkill
- deep-diveSkill
- docsSkill
- incident-debugSkill
- planSkill
- qaSkill
- ralphSkill
- refactor-cleanSkill
- rule-creatorSkill
- security-reviewSkill
- skill-creatorSkill
- tdd-workflowSkill
The file
We split this skill into the rules it gives an agent
1 rule. 0 are common, 1 is distinctive, and 0 are very specific to this project.
0
Common
Most of the 22 edited versions we read keep these.
1
Distinctive
This author's own choices. Worth a look.
0
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 13
If arguments are provided (file paths or PR number), use those as scope
“Common” is measured: kept by at least 6 in 10 of the 22 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
/performance-review
Spawns the performance-reviewer agent to detect performance anti-patterns in your code changes.
Steps
- Gather context — detect the scope of changes to review:
- If arguments are provided (file paths or PR number), use those as scope
- Otherwise, use
git diffto determine what changed - Identify files touching database queries, API endpoints, or data processing
- Spawn the agent — use the Task tool:
Pass in the prompt:Task tool with subagent_type="performance-reviewer"- The diff output and list of changed files
- The project's database ORM and framework context
- Any performance budgets or constraints from project rules
- Present findings — relay the agent's performance report:
- Group by severity: CRITICAL > WARNING
- Include specific code locations and estimated impact
- Show recommended fixes with before/after examples
- Offer follow-up actions:
- "Fix critical issues?" — apply recommended performance fixes
- "Add benchmarks?" — create performance tests for flagged code paths
- "Review again?" — re-run after changes
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.