tomevault-io DLC: Performance Analysis
Run performance checks against the current project and create a GitHub issue with findings.
Before running, read ../dlc/references/ISSUE-TEMPLATE.md now for the issue format, and read ../dlc/references/REPORT-FORMAT.md now for the findings data structure.
Step 1: Identify Performance-Sensitive Areas
Scan the project to determine which performance checks are applicable:
| Indicator | Check Type | Tools |
|---|---|---|
webpack.config.* / vite.config.* / next.config.* |
Bundle analysis | webpack-bundle-analyzer, vite-bundle-analyzer, @next/bundle-analyzer |
lighthouse in deps or CI config |
Lighthouse | lighthouse CLI |
bench / benchmark dirs or scripts |
Benchmarks | Project-specific (e.g. vitest bench, cargo bench, go test -bench) |
docker-compose* / Dockerfile |
Container analysis | dive, docker image inspect |
tsconfig.json / package.json (with build scripts) |
Build time | Time the build command |
Step 2: Run Performance Tools
Bundle Analysis (Web Projects)
Select the tool based on detected build config — run only the first matching tool:
# Detect bundler and run the matching analysis
if [ -f webpack.config.js ] || [ -f webpack.config.ts ]; then
npx webpack --json 2>/dev/null | jq '.assets[] | {name, size}'
elif [ -f vite.config.js ] || [ -f vite.config.ts ]; then
npx vite build --report 2>/dev/null
elif [ -f next.config.js ] || [ -f next.config.mjs ]; then
ANALYZE=true npx next build 2>/dev/null
fi
Lighthouse (Web Projects)
# If lighthouse CLI available and there's a dev server or static build
lighthouse http://localhost:3000 --output=json --quiet 2>/dev/null
Benchmarks
# Node.js
npx vitest bench --reporter=json 2>/dev/null
# Rust
cargo bench 2>/dev/null
# Go
go test -bench=. -benchmem ./... 2>/dev/null
# Python
python -m pytest --benchmark-only 2>/dev/null
Build Time Analysis
# Time the build
time npm run build 2>&1
# or
time cargo build --release 2>&1
Claude Algorithmic Analysis (Always Run)
Even with tools, always perform manual analysis. Use the Explore agent to discover performance-sensitive areas across the codebase (hot paths, data pipelines, request handlers). Use repomix-explorer (if available) for large codebases to get a structural overview. Then use targeted Grep and Read for detailed analysis:
- Search for
O(n^2)or worse patterns: nested loops over the same collection, repeated array searches - Check for missing indexes in database queries (
*.sql, ORM query files) - Look for synchronous blocking in async contexts
- Identify N+1 query patterns in data-fetching code
- Check for unbounded data structures (lists that grow without limit)
- Review hot paths: request handlers, event loops, data pipelines
Step 3: Classify Findings
Map results to the findings format from REPORT-FORMAT.md.
Severity mapping (reinforced here for defense-in-depth):
| Finding Type | Severity |
|---|---|
| Bundle size regression > 50% | Critical |
| O(n^3) or worse in hot path | Critical |
| Lighthouse performance score < 50 | High |
| O(n^2) in frequently-called code | High |
| Bundle size > project target | Medium |
| Missing database indexes on queried columns | Medium |
| Synchronous blocking in async context | Medium |
| Minor optimization opportunities | Low |
| Benchmark results (informational) | Info |
Step 4: Create GitHub Issue
Read ../dlc/references/ISSUE-TEMPLATE.md now and format the issue body exactly as specified.
Critical format rules (reinforced here):
- Title:
[DLC] Performance: {summary of top finding} - Label:
dlc-perf - Body must contain: Scan Metadata table, Findings Summary table (severity x count), Findings Detail grouped by severity, Recommended Actions, Raw Output in collapsed details
REPO=$(gh repo view --json nameWithOwner -q .nameWithOwner)
BRANCH=$(git branch --show-current)
TIMESTAMP=$(date +%s)
BODY_FILE="/tmp/dlc-issue-${TIMESTAMP}.md"
gh issue create \
--repo "$REPO" \
--title "[DLC] Performance: {summary}" \
--body-file "$BODY_FILE" \
--label "dlc-perf"
If issue creation fails, save draft to /tmp/dlc-draft-${TIMESTAMP}.md and print the path.
Step 5: Report
Performance analysis complete.
- Checks run: {list of applicable checks}
- Tools used: {list}
- Findings: {critical} critical, {high} high, {medium} medium
- Issue: #{number} ({url})
If no findings, skip issue creation and report: "No performance issues found."
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