Enforce performance budgets in CI
SkillDocs & knowledgeThe performance-budget skill guides an AI agent through defining and documenting performance budgets for a web service or application. It helps set performance targets, define SLOs for latency or throughput, establish Core Web Vitals targets, create a performance baseline, and document a performance regression policy. The result is a structured performance budget document that the agent can use during code review to check page weight limits like bundle size and load speed.
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Details
Instructions available. Your AI can read the instructions. Execution depends on the setup they require.
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Have a web service or application with measurable performance characteristics.
What your AI can do with it
- Set performance targets for latency, throughput, and page weight
- Define SLOs for latency or throughput
- Establish Core Web Vitals targets
- Create a performance baseline for a web service or application
- Document a performance regression policy
- Check bundle size and load speed limits during code review
Getting started
- Have a web service or application with measurable performance characteristics.
- Ask the agent to set performance targets, define SLOs, or establish Core Web Vitals targets.
- Provide any existing performance data or baseline measurements if available.
- Review the structured performance budget document the agent produces.
- Use the documented budget during code review to check page weight limits like bundle size and load speed.
What this skill tells your AI
The instructions your AI receives, as published by mohitagw15856/pm-claude-skills in skills/performance-budget/SKILL.md and read by ahel’s review.
Without automated enforcement, performance degrades gradually — each PR adds a small library, each feature adds a few KB, and within months the app that loaded in 2 seconds now takes 5. Performance budgets make regressions visible at PR time rather than after user complaints. Catching 'this PR added 200KB to the bundle' in review is far cheaper than debugging a slow production site.
Quick Reference
- Define specific thresholds: max bundle size, min Lighthouse score, max LCP time
- Fail CI when budgets are exceeded to prevent performance regressions
- Size budgets catch accidental heavy dependencies; Lighthouse budgets catch runtime regressions
- Start with loose budgets and tighten them as you optimize
- Monitor production RUM so regressions are caught after deploy, not only in CI
Check
Does this project have performance budgets defined? Check package.json and CI configuration for size or Lighthouse thresholds.
Fix
Set up bundle size limits with size-limit and Lighthouse CI assertions in the CI pipeline.
Explain
Explain performance budgets, how to choose appropriate thresholds, and how to enforce them with size-limit and Lighthouse CI.
Code Review
Inspect CI workflows, package.json, and Lighthouse or bundle-size config for explicit thresholds. Flag repos where budgets are missing, too loose to catch regressions, or unenforced on pull requests. Check whether production RUM and alerting are wired to detect regressions after release.
For full implementation details, code examples, and framework-specific guidance,
see references/rule.md.
Rule page: https://frontendchecklist.io/en/rules/testing/performance-budget
Signals
- GitHub stars
- 1k
- Forks
- 251
- Last commit
- Sep 2026
ahel review
K1binfo
installs-packages (in references/rule.md)
Automated review, not a security audit. Ruleset v1+k2.
Questions
- What kind of performance targets can this skill help set?
- It helps set performance targets, define SLOs for latency or throughput, establish Core Web Vitals targets, create a performance baseline, and document a performance regression policy.
- Does this skill check performance during code review?
- Yes. It guides the agent to check page weight limits like bundle size and load speed during code review.
Advanced
- Item type
- skill
- Key
performance-budget- Source
- github.com/mohitagw15856/pm-claude-skills
github.com/mohitagw15856/pm-claude-skills
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