audit-engineering-productivity
Skill2 starsChanged 9 months agoApache-2.0View on GitHub
Run a single-session engineering productivity audit on the codebase
- Reads credentials
We split this skill into the rules it gives an agent
11 rules. About 0 are common, 7 are distinctive, and 4 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈7
Distinctive · estimate
This author's own choices. Worth a look.
4
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 146
Dependency constraints: All 3 agents are independent -- no ordering required.
- Distinctive: line 158
Check for setup/doctor automation scripts
- Distinctive: line 166
Search for correlation ID patterns
- Distinctive: line 168
Check Sentry integration in logger
- Distinctive: line 173
Check Firebase persistence configuration
- Distinctive: line 174
Look for service worker implementation
- Distinctive: line 176
Search for write queue patterns
- Very specific: line 304
Check docs/audits/single-session/engineering-productivity/ for prior findings and track carryover issues.
- Very specific: line 335
When you only need to audit code quality — use /audit-code instead
- Very specific: line 336
When you need CI/CD pipeline health — use /audit-process instead
- Very specific: line 337
When you need a comprehensive multi-domain audit — use /audit-comprehensive
≈ “Common” is an estimate: at least 1 in 5 of the 308,232 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Single-Session Engineering Productivity Audit
Purpose
Evaluates developer experience (DX), debugging capabilities, and offline support infrastructure. Identifies friction points in development workflows and provides actionable recommendations for improvement.
Execution Mode Selection
| Condition | Mode | Time |
| Task tool available + no context pressure | Parallel | ~15 min |
| Task tool unavailable | Sequential | ~45 min |
| Context running low (<20% remaining) | Sequential | ~45 min |
| User requests sequential | Sequential | ~45 min |
Section A: Parallel Architecture (3 Agents)
When to use: Task tool available, sufficient context budget
Step 0: Load False Positives
# Read false positives to avoid re-flagging known issues
cat docs/technical-debt/FALSE_POSITIVES.jsonl 2>/dev/nullAgent 1: dx-golden-path-auditor
Focus Areas:
- Developer onboarding friction
- npm scripts completeness
- Setup automation (doctor scripts, env validation)
- Development workflow ergonomics
Files:
package.json(scripts section)scripts/directory.env.example,.env.localREADME.md,DEVELOPMENT.md
Checks:
# Count npm scripts
grep -c '"[^"]*":' package.json
# Check for setup/doctor scripts
ls scripts/*.js 2>/dev/null | grep -E 'setup|doctor|verify'
# Check for dev:offline script
grep -c "dev:offline" package.jsonAgent 2: debugging-ergonomics-auditor
Focus Areas:
- Structured logging vs console.log ratio
- Correlation ID support for request tracing
- Error message quality and user guidance
- Sentry integration completeness
Files:
lib/logger.ts*.ts*.tsxfiles (console.log patterns)functions/src/**/*.ts(Cloud Functions logging)app/**/error.tsx(error boundaries)
Checks:
# Console.log to logger ratio
echo "Console.log calls:"
grep -r "console.log" --include="*.ts" --include="*.tsx" app/ lib/ components/ | wc -l
echo "Logger calls:"
grep -r "logger\." --include="*.ts" --include="*.tsx" app/ lib/ components/ | wc -l
# Correlation ID patterns
grep -r "correlationId\|correlation-id\|x-request-id" --include="*.ts" .Agent 3: offline-support-auditor
Focus Areas:
- Firebase IndexedDB persistence configuration
- Service worker presence and functionality
- Offline write queue implementation
- Network status indicators and user feedback
Files:
lib/firebase.tspublic/sw.js(if exists)components/status/offline-indicator.tsxlib/offline-queue.ts(if exists)
Checks:
# Firebase persistence
grep -r "enableIndexedDbPersistence\|enablePersistence" lib/ app/
# Service worker
ls -la public/sw.js 2>/dev/null || echo "No service worker"
# LocalStorage vs IndexedDB usage
grep -r "localStorage" --include="*.ts" --include="*.tsx" | wc -l
grep -r "indexedDB\|IDB\|Dexie" --include="*.ts" --include="*.tsx" | wc -lParallel Execution Command
Invoke all 3 agents in a SINGLE Task message:
Task 1: dx-golden-path-auditor agent - audit setup, scripts, onboarding Task 2:
debugging-ergonomics-auditor agent - audit logging, error handling Task 3:
offline-support-auditor agent - audit persistence, service workers
Each agent prompt MUST end with:
CRITICAL RETURN PROTOCOL:
- Write findings to the specified output file using Write tool or Bash
- Return ONLY: `COMPLETE: [agent-id] wrote N findings to [output-path]`
- Do NOT return full findings content — orchestrator checks completion via fileDependency constraints: All 3 agents are independent -- no ordering required. Each audits a separate domain and writes to separate output sections.
Section B: Sequential Fallback
When to use: Task tool unavailable, context pressure, or user request
Step 1: Golden Path & DX (10 min)
- Review
package.jsonscripts section - Check for setup/doctor automation scripts
- Verify
.env.examplecompleteness - Assess README setup instructions
- Identify missing "golden path" scripts
Step 2: Debugging Ergonomics (10 min)
- Calculate console.log vs logger ratio
- Search for correlation ID patterns
- Review error boundary implementations
- Check Sentry integration in logger
- Assess error message quality
Step 3: Offline Support (10 min)
- Check Firebase persistence configuration
- Look for service worker implementation
- Review offline indicator component
- Search for write queue patterns
- Assess localStorage vs IndexedDB usage
Output Requirements
Report File
Create docs/audits/single-session/engineering-productivity/audit-report.md:
# Engineering Productivity Audit - {DATE}
## Baselines
| Metric | Value |
| ------------------------ | ----- |
| npm scripts count | X |
| Console.log calls | X |
| Logger calls | X |
| Structured logging ratio | X:Y |
| LocalStorage usages | X |
| IndexedDB usage | X |
| Service worker | Y/N |
| Firebase persistence | Y/N |
## Findings Summary
| Severity | Count | Category |
| -------- | ----- | -------------- |
| S0 | X | - |
| S1 | X | Category names |
| S2 | X | Category names |
| S3 | X | Category names |
## Detailed Findings
### 1. Golden Path & DX
[Findings here]
### 2. Debugging Ergonomics
[Findings here]
### 3. Offline Support
[Findings here]
## Quick Wins (E0-E1)
[Prioritized list of low-effort fixes]
## Recommendations
### Immediate (E0-E1)
[List]
### Short-term (E2)
[List]
### Long-term (E3)
[List]JSONL File
Create
docs/audits/single-session/engineering-productivity/audit-findings.jsonl:
CRITICAL - Use this exact schema:
{
"category": "engineering-productivity",
"title": "Short specific title",
"fingerprint": "engineering-productivity::primary_file::identifier",
"severity": "S0|S1|S2|S3",
"effort": "E0|E1|E2|E3",
"confidence": 75,
"files": ["array/of/file/paths.ts"],
"why_it_matters": "1-3 sentences explaining impact",
"suggested_fix": "Concrete remediation direction",
"acceptance_tests": ["Array of verification steps"],
"evidence": ["code snippet", "grep output", "measurement data"]
}Category Definitions
| Category | Description |
| GoldenPath | Setup, scripts, onboarding, dev workflow |
| Debugging | Logging, tracing, error handling, messages |
| Offline | Persistence, service workers, queues, sync |
Severity Scale
| Level | Name | Definition |
| S0 | Critical | Data loss risk, production breaking |
| S1 | High | Significant dev friction, missing core |
| S2 | Medium | Maintainability drag, inconsistency |
| S3 | Low | Polish, minor improvements, nice-to-have |
Effort Scale
| Level | Name | Definition |
| E0 | Minutes | Quick fix, trivial change |
| E1 | Hours | Single-session work |
| E2 | Days | 1-3 days or staged PR |
| E3 | Weeks | Multi-PR, multi-week effort |
Prior Audit Reference
Check docs/audits/single-session/engineering-productivity/ for prior findings
and track carryover issues.
Standard Audit Procedures
Read
.claude/skills/_shared/AUDIT_TEMPLATE.mdfor: Evidence Requirements, Dual-Pass Verification, Cross-Reference Validation, JSONL Output Format, Context Recovery, Post-Audit Validation, MASTER_DEBT Cross-Reference, Interactive Review, TDMS Intake & Commit, Documentation References, Agent Return Protocol, and Honesty Guardrails.
Skill-specific TDMS intake:
node scripts/debt/intake-audit.js \
docs/audits/single-session/engineering-productivity/audit-findings.jsonl \
--source "audit-engineering-productivity-$(date +%Y-%m-%d)"When to Use
- User explicitly invokes
/audit-engineering-productivity - Engineering productivity or DX audit is needed
- Called as part of
/audit-comprehensive(Stage 2)
When NOT to Use
- When you only need to audit code quality — use
/audit-codeinstead - When you need CI/CD pipeline health — use
/audit-processinstead - When you need a comprehensive multi-domain audit — use
/audit-comprehensive
Related Skills
/audit-comprehensive- Run all 7 domain audits/audit-process- CI/CD and automation audit (overlaps with DX)/audit-code- Code quality audit
Version History
| Version | Date | Description |
| 1.1 | 2026-02-23 | Add mandatory MASTER_DEBT cross-reference step before interactive review |
| 1.0 | 2026-02-03 | Initial skill creation |
In this repository81 other files it gives its agents.
- AGENTS.mdAGENTS.md
- CLAUDE.mdCLAUDE.md
- .github/copilot-instructions.mdCopilot instructions
- llms.txtllms.txt
- find-skillsSkill
- add-debtSkill
- alertsSkill
- analyzeSkill
- artifacts-builderSkill
- audit-agent-qualitySkill
- audit-aggregatorSkill
- audit-ai-optimizationSkill
- audit-codeSkill
- audit-comprehensiveSkill
- audit-documentationSkill
- audit-enhancementsSkill
- audit-healthSkill
- audit-performanceSkill
- audit-processSkill
- audit-refactoringSkill
- audit-securitySkill
- brainstormSkill
- checkpointSkill
- code-reviewerSkill
- comprehensive-ecosystem-auditSkill
- content-research-writerSkill
- convergence-loopSkill
- create-auditSkill
- data-effectiveness-auditSkill
- debt-runnerSkill
- decrypt-secretsSkill
- deep-planSkill
- deep-researchSkill
- developer-growth-analysisSkill
- doc-ecosystem-auditSkill
- doc-optimizerSkill
- docs-maintainSkill
- document-analysisSkill
- ecosystem-healthSkill
- Excel AnalysisSkill
- find-skillsSkill
- frontend-designSkill
- gh-fix-ciSkill
- github-healthSkill
- health-ecosystem-auditSkill
- hook-ecosystem-auditSkill
- market-research-reportsSkill
- mcp-builderSkill
- media-analysisSkill
- multi-ai-auditSkill
- pre-commit-fixerSkill
- pr-ecosystem-auditSkill
- pr-retroSkill
- pr-reviewSkill
- quick-fixSkill
- recallSkill
- repo-analysisSkill
- repo-synthesisSkill
- script-ecosystem-auditSkill
- session-beginSkill
- The first 60 shown.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
Reviews can't be read right now.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

