CI Perf Lint

Repository-first CI audit across major CI platforms.

CI Perf Lint scans workflows plus repository context, prioritizes CI waste, and produces a shareable improvement plan with measurement hints and AI-ready handoff instructions.

It does not just list warnings. It tells you what to fix first.

Quick Start

Run once against a repository:

# recommended (faster startup)
bunx ci-perf-lint
# or
npx ci-perf-lint

Pipe directly into AI tools:

bunx ci-perf-lint | opencode
bunx ci-perf-lint | claude -p "Apply the findings above to fix workflows"
bunx ci-perf-lint | gemini
bunx ci-perf-lint | codex exec

Install globally for repeated use:

bun install -g ci-perf-lint
# or
npm install -g ci-perf-lint

What You Get

Each run returns:

• Top findings
• What to fix first
• Measurement hints
• AI-ready handoff

The output is designed to be:

• readable by humans
• directly usable by AI
• easy to paste into Slack, issues, or PRs

When To Use This

Use CI Perf Lint when:

• CI has become slow
• runner cost needs review
• PR feedback loops are too long
• workflows have accumulated over time
• you need a quick CI improvement report
• you want to safely delegate fixes to AI

This is not a daily lint tool. It is a high-value audit tool for CI owners.

Example Output

CI Perf Lint
Repository: acme/api
Workflows scanned: 5

Top findings

1. missing-path-ignore-for-non-code
   Context: docs/, *.md, and *.txt changes trigger full CI in 3 workflows
   Why it matters: avoidable runs increase runner cost and PR latency
   Suggested action: add paths-ignore for non-code files
   Measurement hint: confirm docs-only PR skips all heavy workflows

2. duplicate-install-or-lint
   Context: npm install runs in both ci.yml and lint.yml
   Why it matters: repeated dependency installs add cost and delay feedback
   Suggested action: consolidate into a shared job or reuse artifacts
   Measurement hint: compare total workflow duration before and after

3. missing-dependency-cache
   Context: actions/setup-node used without cache in 2 workflows
   Why it matters: install cost is paid on every run
   Suggested action: enable package-manager-aware caching
   Measurement hint: compare install step duration

4. avoid-svg-component-imports (src/icons.tsx:12:1 +3 more) [repository-wide source/tooling]
   Context: avoid-svg-component-imports appears in 4 source/tooling locations; apply one consistent fix pattern where appropriate.
   Why it matters: SVG component imports can increase transform cost and module count when plain asset URLs would be enough.
   Suggested action: replace ordinary SVG component imports with asset URL imports where dynamic component behavior is not needed
   Measurement hint: compare transform time, bundle/module counts, and build output before and after

Repository-First Approach

CI Perf Lint is designed as a repository-level audit tool.

Default scope:

• workflows under .github/workflows/
• repository-level context such as configuration, structure, and cross-workflow patterns

Repository context includes signals such as:

• duplicated logic across workflows
• inconsistent caching strategies
• repo-level tool usage
• trigger patterns across workflows

Typical flow:

1. scan the repository and workflows
2. identify repository-wide waste patterns
3. prioritize top improvements
4. optionally drill down per workflow

CI inefficiencies are often repository-wide:

• docs changes trigger multiple workflows
• similar lint or setup logic is duplicated across files
• caching strategy differs between workflows
• only some workflows use concurrency controls

Human + AI Workflow

CI Perf Lint separates CI optimization into two phases:

1. Deterministic audit
2. AI-driven implementation

Typical usage:

1. run the audit
2. review top findings
3. pipe output to AI or copy and paste it
4. apply fixes
5. verify using measurement hints

Why Not Just Ask AI?

You can.

CI Perf Lint improves that workflow by:

• avoiding repeated context reconstruction
• providing deterministic findings
• separating higher-confidence issues from broader suggestions
• including measurement steps for verification

AI becomes more reliable when given structured constraints.

Usage

Default run:

ci-perf-lint

Render AI handoff:

ci-perf-lint . --format handoff

Include exploratory suggestions:

ci-perf-lint . --mode exploratory

Markdown output:

ci-perf-lint . --format markdown

JSON output:

ci-perf-lint . --format json --top 10

Focus modes:

ci-perf-lint . --workflow-only
ci-perf-lint . --repository-only

Show selected workflows:

ci-perf-lint . --show-workflows

Strict mode shows higher-confidence warnings by default. Exploratory mode also includes broader suggestions.

Current Scope

CI Perf Lint includes dozens of rules covering:

• trigger conditions
• concurrency
• dependency caching
• checkout patterns
• duplicate steps
• Docker build patterns
• language-specific CI optimizations
• AI-oriented migration suggestions

See https://ci-perf-lint.veritycost.com/rules/ for the current rule index.

Positioning

CI Perf Lint is:

• not a correctness linter
• not a runtime profiler
• not a generic AI wrapper

It is a static analyzer for CI/CD waste, designed to produce actionable, shareable improvement plans.

Development

bun run lint
bun run audit:static
bun test --parallel

Summary

CI Perf Lint tells you:

• what to fix
• what to fix first
• how to verify it
• how to safely apply it with AI