About performance-budget
A skill for drafting an actionable performance budget for web services and applications. It helps teams define measurable frontend and backend limits, measurement methods, CI enforcement, and responses to breaches.
Key features
- 01Frontend and backend performance targets
- 02Budgets for user journeys and assets
- 03Measurement and monitoring guidance
- 04CI performance enforcement gates
- 05Breach severity and response process
Use cases
- 01Set limits for critical user journeys
- 02Add performance checks to CI/CD
- 03Define team actions when targets are exceeded
Install
Copy the command and run it in a terminal.
npx skills add https:/ / github.com/ mohitagw15856/ pm-claude-skills --skill performance-budgetAfter installing, type/performance-budgetin Claude Code to confirm it loaded.
Details
From the project READMEPerformance Budget Skill
Produce a complete, actionable performance budget document for a web service or application. A performance budget is not a wishlist — it is a set of measurable, enforced constraints that define what "acceptable performance" means and who is responsible when those constraints are violated.
A good performance budget answers: what are the targets, how are they measured, what triggers an investigation, and what happens when a budget is breached.
Required Inputs
Ask for these if not already provided:
- Service name and type — web app, API service, mobile app, or combination
- Key user journeys — the 3–5 most important flows users take (e.g. "search → product page → checkout")
- Current baseline metrics — P50/P95/P99 latency, LCP, CLS, INP if available (state "no baseline" if not collected yet)
- Tech stack — frontend framework, backend language/framework, CDN, database
- Deployment environment — cloud provider, region(s), edge/CDN configuration
- Cost constraints — any budget or infrastructure limits that affect headroom
Output Format
Performance Budget: [Service Name]
Service: [Name] | Team: [Team name] Last updated: [Date] | Owner: [Name / role] Environment: [Production / Staging baseline] | Review cadence: [Quarterly / per-sprint]
Overview
[2–3 sentences describing the service, its user-facing performance requirements, and why performance is a priority. Reference the business impact of latency — e.g. conversion rate, user retention, SLA obligations.]
Performance philosophy: [e.g. "Performance is a feature. Every engineer is responsible for keeping the service within budget. Regressions must be caught in CI before they reach production."]
Key User Journeys
Define the critical paths that the performance budget is designed to protect.
| Journey ID | Journey name | Entry point | Exit point | Criticality |
|---|---|---|---|---|
| UJ-1 | [e.g. New user sign-up] | [Landing page] | [Dashboard] | Critical |
| UJ-2 | [e.g. Core workflow task] | [e.g. /app/tasks] | [e.g. Task complete] | High |
| UJ-3 | [e.g. Search and select] | [e.g. /search] | [e.g. Detail page] | High |
| UJ-4 | [e.g. API data fetch] | [e.g. GET /api/items] | [e.g. 200 response] | Medium |
Frontend Performance Budget
Complete this section for web and mobile applications. Skip for API-only services.
Core Web Vitals Targets
Targets apply to the 75th percentile of real user sessions (field data), measured on a mid-range Android device on a 4G connection unless otherwise stated.
| Metric | Description | Good | Needs Improvement | Poor | Our Target | Current baseline |
|---|---|---|---|---|---|---|
| LCP | Largest Contentful Paint — perceived load speed | ≤2.5s | 2.5–4.0s | >4.0s | [≤X.Xs] | [Xs / not measured] |
| INP | Interaction to Next Paint — responsiveness | ≤200ms | 200–500ms | >500ms | [≤Xms] | [Xms / not measured] |
| CLS | Cumulative Layout Shift — visual stability | ≤0.1 | 0.1–0.25 | >0.25 | [≤0.X] | [X.XX / not measured] |
| FCP | First Contentful Paint | ≤1.8s | 1.8–3.0s | >3.0s | [≤X.Xs] | [Xs / not measured] |
| TTFB | Time to First Byte | ≤800ms | 800ms–1.8s | >1.8s | [≤Xms] | [Xms / not measured] |
Page Weight Budget
| Asset type | Max size (compressed) | Current | Status |
|---|---|---|---|
| Total page weight | [e.g. 500KB] | [XKB / unknown] | [Within / Over / Unknown] |
| JavaScript (initial load) | [e.g. 200KB] | [XKB / unknown] | [Within / Over / Unknown] |
| CSS | [e.g. 50KB] | [XKB / unknown] | [Within / Over / Unknown] |
| Images (above fold) | [e.g. 150KB] | [XKB / unknown] | [Within / Over / Unknown] |
| Web fonts | [e.g. 50KB] | [XKB / unknown] | [Within / Over / Unknown] |
| Third-party scripts | [e.g. 100KB] | [XKB / unknown] | [Within / Over / Unknown] |
Per-Journey Frontend Targets
| Journey | LCP | INP | CLS | FCP | TTFB |
|---|---|---|---|---|---|
| UJ-1: [Journey name] | [≤Xs] | [≤Xms] | [≤0.X] | [≤Xs] | [≤Xms] |
| UJ-2: [Journey name] | [≤Xs] | [≤Xms] | [≤0.X] | [≤Xs] | [≤Xms] |
| UJ-3: [Journey name] | [≤Xs] | [≤Xms] | [≤0.X] | [≤Xs] | [≤Xms] |
Backend Performance Budget
API Latency SLOs
Targets measured at the service boundary (not including client-side network latency).
| Endpoint / operation | Method | P50 | P95 | P99 | Max (hard limit) | Error rate |
|---|---|---|---|---|---|---|
| [e.g. /api/auth/login] | POST | [≤Xms] | [≤Xms] | [≤Xms] | [≤Xms] | [<X%] |
| [e.g. /api/items] | GET | [≤Xms] | [≤Xms] | [≤Xms] | [≤Xms] | [<X%] |
| [e.g. /api/items/:id] | GET | [≤Xms] | [≤Xms] | [≤Xms] | [≤Xms] | [<X%] |
| [e.g. /api/items] | POST | [≤Xms] | [≤Xms] | [≤Xms] | [≤Xms] | [<X%] |
| [e.g. Background job: sync] | — | [≤Xs] | [≤Xs] | [≤Xs] | [≤Xs] | [<X%] |
Overall service SLOs:
| SLO | Target | Measurement window |
|---|---|---|
| Availability | [99.X%] | 30-day rolling |
| P95 latency (all endpoints) | [≤Xms] | 30-day rolling |
| Error rate (5xx) | [<X%] | 30-day rolling |
| Throughput (sustained) | [≥X req/s] | Peak hour |
Database Query Budget
| Query / operation | P50 | P95 | Max | Notes |
|---|---|---|---|---|
| [e.g. User lookup by ID] | [≤Xms] | [≤Xms] | [≤Xms] | Index on user_id |
| [e.g. List items for user] | [≤Xms] | [≤Xms] | [≤Xms] | Paginated, max 100 rows |
| [e.g. Full-text search] | [≤Xms] | [≤Xms] | [≤Xms] | Elasticsearch / pg_trgm |
Measurement Methodology
Real User Monitoring (RUM)
Tool: [e.g. Google CrUX, SpeedCurve, Datadog RUM, Sentry Performance, custom] Data source: [Field data from real users / Lab data from synthetic tests / Both] Sample rate: [X% of sessions] How to access: [Dashboard URL or tool access instructions]
What is measured:
- Core Web Vitals (LCP, INP, CLS) per page and journey
- Custom performance marks for business-critical interactions
- Resource timing for key assets
- Long tasks (>50ms on main thread)
Synthetic Monitoring
Tool: [e.g. Lighthouse CI, WebPageTest, k6, Artillery, Playwright with performance assertions] Frequency: [Every X minutes / on every deploy / nightly] Test location(s): [e.g. eu-west-1, us-east-1] Device profile: [Desktop 10Mbps / Mobile 4G Moto G4 / both]
Synthetic test suite location: [Link to test files]
Backend Observability
APM tool: [e.g. Datadog, Grafana + Prometheus, New Relic, AWS X-Ray] Metrics collected:
- Request rate, error rate, duration (RED metrics) per endpoint
- Database query duration and connection pool utilisation
- Cache hit/miss rates
- Background job queue depth and processing latency
Dashboard: [Link to primary performance dashboard]
CI/CD Performance Enforcement
Performance budgets are enforced at two gates:
Gate 1 — Build-time Bundle Analysis
Tool: [e.g. bundlesize, size-limit, webpack-bundle-analyzer with CI assertion]
Config file: [[.bundlesizerc / .size-limit.js / etc.]]
Trigger: Every PR targeting main
Blocking: Yes — PR cannot merge if bundle size budget is exceeded
// Example .size-limit.js
[
{
"path": "dist/js/*.js",
"limit": "200 KB"
},
{
"path": "dist/css/*.css",
"limit": "50 KB"
}
]
Gate 2 — Synthetic Performance Tests in CI
Tool: [e.g. Lighthouse CI, k6, Artillery] Trigger: On deploy to staging Blocking: Yes — production deploy is blocked if thresholds fail Thresholds checked:
- LCP ≤ [Xs]
- CLS ≤ [0.X]
- P95 API latency ≤ [Xms]
- Error rate < [X%]
CI config location: [[.github/workflows/perf.yml / ci/performance.yaml]]
How to run locally:
# Run Lighthouse CI against local build
[command — e.g. lhci autorun --config=lighthouserc.js]
# Run load test locally
[command — e.g. k6 run load-tests/api-smoke.js]
Budget Breach Response Process
A budget breach is when a measured metric exceeds its target for [X consecutive measurements / X minutes sustained / a single deploy].
Breach Severity Levels
| Severity | Condition | Response time | Who acts |
|---|---|---|---|
| P1 — Critical | >2× budget threshold in production | Immediate | On-call engineer + team lead |
| P2 — High | >1.5× budget threshold in production | Within 4 hours | On-call engineer |
| P3 — Medium | Threshold exceeded in production | Within 1 sprint | PR author + team |
| P4 — Low | Threshold exceeded in staging only | Before merge | PR author |
Breach Investigation Checklist
When a breach is detected, work through this checklist in order:
1. Identify the regression commit
# Compare performance across recent deploys
[command — e.g. datadog metrics query, lighthouse-ci compare, git bisect]
2. Classify the breach
- Is this a code change? (new feature, refactor, dependency bump)
- Is this an infrastructure change? (new instance type, config change)
- Is this an external factor? (CDN issue, DNS, upstream dependency)
- Is this a measurement anomaly? (test environment issue, sample size)
3. Immediate actions
- If P1/P2 in production and a code cause is confirmed: roll back or disable the feature flag
- If cause is unknown: do not roll back immediately — gather more data first
- Notify [#performance / #incidents Slack channel] with: metric name, current value, budget target, suspected cause
4. Resolution
- Fix the root cause — do not just adjust the budget threshold
- Budget thresholds should only change after a team discussion and explicit approval from [tech lead / EM]
- Document the breach in the [performance log / incident record]
Budget change policy: Budget thresholds may only be relaxed if: (a) the feature delivering the regression has measurable business value that outweighs the performance cost, and (b) the change is reviewed and approved by [tech lead].
Performance Review Cadence
| Trigger | Action |
|---|---|
| Every sprint | Review P95/P99 latency trends; flag any creeping degradation |
| Every quarter | Full performance budget review — update baselines, adjust targets, audit tooling |
| After major feature launch | Re-measure all Core Web Vitals and API SLOs; update baselines |
| After infrastructure change | Re-run full synthetic test suite; confirm no regression |
| After dependency upgrade | Run bundle size diff; confirm no unexpected size increase |
Next scheduled review: [Date] Review owner: [Name / role]
Quality Checks
- Every budget threshold is a specific number — not a range or "TBD"
- Both frontend (if applicable) and backend targets are defined — not just one or the other
- Measurement tooling is named with a link to the dashboard or config file
- CI enforcement is configured for at least one gate (build-time or deploy-time)
- Budget breach response process names specific Slack channels and owners
- Budget thresholds are anchored to baseline measurements or a justified target — not pulled from thin air
- Per-journey targets are defined for critical user journeys, not just global averages
Anti-Patterns
- Do not set budget thresholds without measuring a current baseline first — targets must be anchored to reality
- Do not define global averages only — critical user journeys need individual budgets as they may diverge significantly
- Do not omit CI enforcement — a performance budget that is not enforced in the build pipeline will not be respected
- Do not leave the breach response process without named owners and escalation channels
- Do not set budgets that apply only to one environment — production and staging targets should be documented separately if they differ