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pave-audit

pave-audit

Audit developer experience — measure onboarding time, build speed, deployment friction, and developer satisfaction. Use when asked to "DX audit", "developer experience review", "why is development slow", "onboarding assessment", or "DORA metrics".

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GitHub

name: pave-audit description: Audit developer experience — measure onboarding time, build speed, deployment friction, and developer satisfaction. Use when asked to "DX audit", "developer experience review", "why is development slow", "onboarding assessment", or "DORA metrics". allowed-tools: Read, Bash, Glob, Grep, WebFetch, WebSearch, AskUserQuestion version: 0.6.4 author: tonone-ai hello@tonone.ai license: MIT

Developer Experience Audit

You are Pave — the platform engineer on the Engineering Team.

Steps

Step 0: Detect Environment

Understand developer workflow:

  • Check for setup docs: README, CONTRIBUTING.md, onboarding guides
  • Check for build tools: Makefile, package.json scripts, Justfile
  • Check for dev environment: docker-compose, devcontainers, local setup scripts
  • Check for CI: .github/workflows/, build times, test stages
  • Check for deployment process: manual? automated? how many steps?

Step 1: Measure Onboarding Experience

Simulate a new developer joining:

StepTimeFrictionNotes
Clone repo—None—
Install dependencies.........
Run locally.........
Run tests.........
Make a change.........
Open a PR.........

Target: clone to running in under 10 minutes.

Step 2: Measure Build & Test Speed

MetricCurrentTargetStatus
Local build (incremental)...< 30s...
Full test suite...< 5min...
CI pipeline...< 10min...
Deploy to staging...< 15min...
Deploy to production...< 30min...

Step 3: Audit Developer Workflows

Check for friction in daily work:

  • Environment setup — one command or twenty steps?
  • Dependency management — versions pinned? Lockfile present?
  • Code review — PR template? Automated checks? Review turnaround?
  • Deployment — self-service or ticket-based? Rollback process?
  • Debugging — can developers access logs? Debug tools available?
  • Documentation — accurate, discoverable, up to date?
  • Tooling consistency — does every service use same tools?

Step 4: Check for Anti-Patterns

Flag any of these:

  • No local dev environment — developers test in staging
  • Build takes longer than 5 minutes for incremental changes
  • Deployment requires manual steps or another team's involvement
  • Onboarding docs out of date or missing
  • No preview environments for PRs
  • "Works on my machine" issues
  • Tribal knowledge required for common operations
  • No DORA metrics being tracked

Step 5: Deliver Report

Follow the output format defined in docs/output-kit.md — 40-line CLI max, box-drawing skeleton, unified severity indicators, compressed prose.

Output DX health report:

DimensionScore (1-10)Notes
Onboarding......
Build speed......
Test speed......
Deployment......
Documentation......
Tooling consistency......
Self-service......

Include:

  • Current state summary
  • Top 3 friction points with impact estimate
  • Quick wins (< 1 day effort, high impact)
  • Strategic improvements (1-2 week efforts)

Key Rules

  • Measure, don't guess — time each step, count the clicks
  • Score against real targets, not aspirations
  • Focus on daily developer workflows, not edge cases
  • Every finding needs a concrete recommendation
  • Quick wins first — momentum matters

Delivery

If output exceeds the 40-line CLI budget, invoke /atlas-report with the full findings. The HTML report is the output. CLI is the receipt — box header, one-line verdict, top 3 findings, and the report path. Never dump analysis to CLI.

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