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QA Docs Coverage (Jan 2026) - Discovery, Freshness, and Runbook Quality

Modern Best Practices (January 2026)

• Docs as QA : Treat docs as production artifacts with owners, review cadence, and CI quality gates (links/style/contracts/freshness)
• Contract-first : Validate OpenAPI/AsyncAPI/JSON Schema in CI; use coverage tools (Swagger Coverage / OpenAPI Coverage) to detect gaps
• Runbook testability : Every runbook must be executable in staging; validate with synthetic tests and incident exercises
• Automation + observability : Track coverage %, freshness, and drift via CI dashboards; prevent regressions via PR checklists

This skill provides operational workflows for auditing existing codebases, identifying documentation gaps, and systematically generating missing documentation. It complements docs-codebase by providing the discovery and analysis layer.

Key Principle : Templates exist in docs-codebase. This skill tells you what to document and how to find undocumented components.

Core references: Diataxis (doc structure), OpenAPI (REST), AsyncAPI (events).

When to use

• Auditing an existing repo for missing/outdated documentation
• Adding documentation quality gates (lint/link checks/contracts/freshness) to CI/CD
• Validating runbooks for incident readiness (MTTR reduction)

When to avoid

• Writing new documentation from scratch without a component inventory (use discovery first)
• Publishing AI-generated docs without human review and command/link verification

Quick start

Use progressive disclosure: load only the reference file you need.

1. Discover components: references/discovery-patterns.md
2. Measure coverage + gaps: references/audit-workflows.md (Phase 1-2) and assets/coverage-report-template.md
3. Prioritize work: references/priority-framework.md
4. Create an actionable backlog: assets/documentation-backlog-template.md and templates in docs-codebase
5. Prevent regression: references/cicd-integration.md and references/freshness-tracking.md

Optional (recommended scripts; run from the repo being audited):

• Local link check: python3 frameworks/shared-skills/skills/qa-docs-coverage/scripts/check_local_links.py docs/
• Freshness report: python3 frameworks/shared-skills/skills/qa-docs-coverage/scripts/docs_freshness_report.py --docs-root docs/

Docs Folder / LLM Iteration Audit (Critical Option)

Use this when any repository has a docs/ folder with many LLM-generated research and implementation artifacts across phases/iterations.

1. Inventory docs and classify by type (Tutorial, How-to, Reference, Explanation).
2. Detect duplicate topics and define one canonical file per topic/feature.
3. Audit claim quality:
   • external claims must include source link + verification date
   • implementation claims must map to current code or decision log
4. Enforce lifecycle metadata for non-canonical docs (status, integrates_into, owner, last_verified, delete_by).
5. Trim aggressively at each phase boundary: integrated drafts must be deleted on schedule; track rare retention exceptions in backlog.

Minimum QA gate for docs folders:

• block merge if a canonical doc is missing for a changed feature
• block merge if delete_by is passed for integrated docs
• block merge on broken links or stale critical docs without owner
• block merge if AGENTS.md or README.md is missing, stale, or not linked to current canonical docs

Large Codebase Audit (100K-1M LOC)

For large codebases, the key principle is: LLMs don't need the entire codebase - they need the right context for the current task.

Phase 0: Context Extraction

Before starting an audit, extract codebase context using tools:

Hierarchical Audit Strategy

For monorepos and large projects, audit hierarchically:

1. Root Level (Week 1)
   ├── AGENTS.md / CLAUDE.md exists?
   ├── README.md quality
   ├── ARCHITECTURE.md exists?
   └── docs/ directory structure

2. Module Level (Week 2-3)
   ├── Each major directory has AGENTS.md?
   ├── API documentation complete?
   └── Service boundaries documented?

3. Component Level (Week 4+)
   ├── Individual component READMEs
   ├── Code comments quality
   └── Test documentation

Cross-Platform Documentation Audit

Check for multi-tool compatibility:

[ ] AGENTS.md exists (cross-platform standard)
[ ] CLAUDE.md exists or symlinked to AGENTS.md
[ ] GEMINI.md symlinked (if using Gemini)
[ ] File size under 300 lines (use @references for depth)
[ ] Subdirectory docs for each major module

Large Codebase Coverage Checklist

LARGE CODEBASE AUDIT CHECKLIST

Context Extraction:
[ ] Generated codebase dump (gitingest/repo2txt)
[ ] Created directory structure overview
[ ] Identified major modules/services

Root Documentation:
[ ] AGENTS.md / CLAUDE.md present and <300 lines
[ ] README.md with quick start
[ ] ARCHITECTURE.md with system overview
[ ] Symlinks configured for cross-platform

Module Documentation:
[ ] Each major directory has AGENTS.md
[ ] API endpoints documented
[ ] Database schemas documented
[ ] Event/message contracts documented

Maintenance:
[ ] Documentation ownership assigned
[ ] Freshness tracking enabled
[ ] CI/CD checks configured

Sources : Anthropic Claude Code Best Practices, OpenAI AGENTS.md Guide

Core QA (Default)

What "Docs as QA" Means

• Treat docs as production quality artifacts: they reduce MTTR, enable safe changes, and define expected behavior.
• REQUIRED doc types for reliability and debugging ergonomics:
  • "How to run locally/CI" and "how to test"
  • Operational runbooks (alerts, common failures, rollback)
  • Service contracts (OpenAPI/AsyncAPI) and schema examples
  • Known issues and limitations (with workarounds)

Coverage Model (Risk-Based)

• Prioritize docs by impact:
  • P1: externally consumed contracts and failure behavior (OpenAPI/AsyncAPI, auth, error codes, SLOs).
  • P2: internal integration and operational workflows (events, jobs, DB schema, runbooks).
  • P3: developer reference (configs, utilities).

Freshness Checks (Prevent Stale Docs)

• Define owners, review cadence, and a "last verified" field for critical docs.
• CI economics:
  • Block PRs only for missing/invalid P1 docs.
  • Warn for P2/P3 gaps; track via backlog.
• Run link checks and linting as fast pre-merge steps.

Runbook Testability

• A runbook is "testable" if a new engineer can follow it and reach a measurable end state.
• Include: prerequisites, exact commands, expected outputs, rollback criteria, and escalation paths.

Do / Avoid

Do :

• Keep docs close to code (same repo) and version them with changes.
• Use contracts and examples as the source of truth for integrations.

Avoid :

• Large ungoverned docs/ folders with no owners and no CI gates.
• Writing runbooks that cannot be executed in a sandbox/staging environment.

Quick Reference

Decision Tree: Documentation Audit Workflow

User needs: [Audit Type]
    ├─ Repo has a docs folder with LLM-generated research/feature docs?
    │   └─ Run Docs Folder / LLM Iteration Audit first, then apply P1/P2/P3 prioritization
    │
    ├─ Starting fresh audit?
    │   ├─ Public-facing APIs? → Priority 1: External-Facing (OpenAPI, webhooks, error codes)
    │   ├─ Internal services/events? → Priority 2: Internal Integration (endpoints, schemas, jobs)
    │   └─ Configuration/utilities? → Priority 3: Developer Reference (options, helpers, constants)
    │
    ├─ Found undocumented component?
    │   ├─ API/Controller? → Scan endpoints → Use api-docs-template → Priority 1
    │   ├─ Service/Handler? → List responsibilities → Document contracts → Priority 2
    │   ├─ Database/Entity? → Generate ER diagram → Document entities → Priority 2
    │   ├─ Event/Message? → Map producer/consumer → Schema + examples → Priority 2
    │   └─ Config/Utility? → Extract options → Defaults + descriptions → Priority 3
    │
    ├─ Large codebase with many gaps?
    │   └─ Use phase-based approach:
    │       1. Discovery Scan → Coverage Analysis
    │       2. Prioritize by impact (P1 → P2 → P3)
    │       3. Generate docs incrementally (critical first)
    │       4. Set up maintenance (PR templates, quarterly audits)
    │
    └─ Maintaining existing docs?
        └─ Check for:
            ├─ Outdated docs (code changed, docs didn't) → Update or remove
            ├─ Orphaned docs (references non-existent code) → Remove
            └─ Missing coverage → Add to backlog → Prioritize

Navigation: Discovery & Analysis

Component Discovery

Resource : references/discovery-patterns.md

Language-specific patterns for discovering documentable components:

• .NET/C# codebase (Controllers, Services, DbContexts, Kafka handlers)
• Node.js/TypeScript codebase (Routes, Services, Models, Middleware)
• Python codebase (Views, Models, Tasks, Config)
• Go, Java/Spring, React/Frontend patterns
• Discovery commands (ripgrep, grep, find)
• Cross-reference discovery (Kafka topics, external APIs, webhooks)

Priority Framework

Resource : references/priority-framework.md

Framework for prioritizing documentation efforts:

• Priority 1: External-Facing (public APIs, webhooks, auth) - Must document
• Priority 2: Internal Integration (services, events, database) - Should document
• Priority 3: Developer Reference (config, utilities) - Nice to have
• Prioritization decision tree
• Documentation debt scoring (formula + interpretation)
• Compliance considerations (ISO 27001, GDPR, HIPAA)

Audit Workflows

Resource : references/audit-workflows.md

Systematic workflows for conducting audits:

• Phase 1: Discovery Scan (identify all components)
• Phase 2: Coverage Analysis (compare against existing docs)
• Phase 3: Generate Documentation (use templates)
• Phase 4: Maintain Coverage (PR templates, CI/CD checks)
• Audit types (full, incremental, targeted)
• Audit checklist (pre-audit, during, post-audit)
• Tools and automation

CI/CD Integration

Resource : references/cicd-integration.md

Automated documentation checks and enforcement:

• PR template documentation checklists
• CI/CD coverage gates (GitHub Actions, GitLab CI, Jenkins)
• Pre-commit hooks (Git, Husky)
• Documentation linters (markdownlint, Vale, link checkers)
• API contract validation (Spectral, AsyncAPI CLI)
• Coverage tools (Swagger Coverage, OpenAPI Coverage)
• Automated coverage reports
• Best practices and anti-patterns

Freshness Tracking

Resource : references/freshness-tracking.md

Track documentation staleness and drift from code:

• Freshness metadata standards (last_verified, owner, review_cadence)
• Git-based freshness analysis scripts
• Staleness thresholds by priority (P1: 30 days, P2: 60 days, P3: 90 days)
• CI/CD freshness gates (GitHub Actions, GitLab CI)
• Observability dashboards and metrics
• Automated doc reminder bots

API Documentation Validation

Resource : references/api-docs-validation.md

Validate API documentation accuracy against live behavior:

• Schema-to-docs drift detection
• Example request/response validation
• Endpoint coverage auditing
• Contract-first documentation workflows

Runbook Testing

Resource : references/runbook-testing.md

Validate operational runbooks are executable and current:

• Runbook testability criteria and scoring
• Synthetic test execution in staging
• Incident exercise integration
• Staleness detection and refresh cadence

Documentation Quality Metrics

Resource : references/documentation-quality-metrics.md

KPIs and dashboards for documentation health:

• Coverage, freshness, and accuracy metrics
• Documentation debt scoring formulas
• CI dashboard integration patterns
• Trend tracking and alerting thresholds

Navigation: Templates

Coverage Report Template

Template : assets/coverage-report-template.md

Structured coverage report with:

• Executive summary (coverage %, key findings, recommendations)
• Coverage by category (API, Service, Data, Events, Infrastructure)
• Gap analysis (P1, P2, P3 with impact/effort)
• Outdated documentation tracking
• Documentation debt score
• Action plan (sprints + ongoing)

Documentation Backlog Template

Template : assets/documentation-backlog-template.md

Backlog tracking with:

• Status summary (In Progress, To Do P1/P2/P3, Blocked, Completed)
• Task organization by priority
• Templates reference (quick links)
• Effort estimates (Low < 2h, Medium 2-8h, High > 8h)
• Review cadence (weekly, bi-weekly, monthly, quarterly)

Output Artifacts

After running an audit, produce these artifacts:

1. Coverage Report - .codex/docs/audit/coverage-report.md

   • Overall coverage percentage
   • Detailed findings by category
   • Gap analysis with priorities
   • Recommendations and next audit date

2. Documentation Backlog - .codex/docs/audit/documentation-backlog.md

   • In Progress items with owners
   • To Do items by priority (P1, P2, P3)
   • Blocked items with resolution path
   • Completed items with dates

3. Generated Documentation - .codex/docs/ (organized by category)

   • API reference (public/private)
   • Event catalog (Kafka/messaging)
   • Database schema (ER diagrams)
   • Background jobs (runbooks)

Integration with Foundation Skills

This skill works closely with:

docs-codebase - Provides templates for:

• api-docs-template.md - REST API documentation
• adr-template.md - Architecture decisions
• readme-template.md - Project overviews
• changelog-template.md - Release history

Workflow :

1. Use qa-docs-coverage to discover gaps
2. Use docs-codebase templates to fill gaps
3. Use qa-docs-coverage CI/CD integration to maintain coverage

Anti-Patterns to Avoid

• Documenting everything at once - Prioritize by impact, document incrementally
• Merging doc drafts without review - Drafts must be validated by owners and runnable in practice
• Ignoring outdated docs - Outdated docs are worse than no docs
• Documentation without ownership - Assign owners for each doc area
• Skipping the audit - Don't assume you know what's documented
• Blocking all PRs - Only block for P1 gaps, warn for P2/P3

Optional: AI / Automation

Do :

• Use AI to draft docs from code and tickets, then require human review and link/command verification.
• Use AI to propose "freshness diffs" and missing doc sections; validate by running the runbook steps.

Avoid :

• Publishing unverified drafts that include incorrect commands, unsafe advice, or hallucinated endpoints.

Success Criteria

Immediate (After Audit) :

• Coverage report clearly shows gaps with priorities
• Documentation backlog is actionable and assigned
• Critical gaps (P1) identified with owners

Short-term (1-2 Sprints) :

• All P1 gaps documented
• Documentation coverage > 80% for external-facing components
• Documentation backlog actively managed

Long-term (Ongoing) :

• Quarterly audits show improving coverage (upward trend)
• PR documentation checklist compliance > 90%
• "How do I" questions in Slack decrease
• Onboarding time for new engineers decreases

Related Skills

• docs-codebase - Templates for writing documentation (README, ADR, API docs, changelog)
• docs-ai-prd - PRD and tech spec templates for new features
• software-code-review - Code review including documentation standards

Usage Notes

For Claude : When auditing a codebase:

1. Start with discovery - Use references/discovery-patterns.md to find components
2. Calculate coverage - Compare discovered components vs existing docs
3. Prioritize gaps - Use references/priority-framework.md to assign P1/P2/P3
4. Follow workflows - Use references/audit-workflows.md for systematic approach
5. Use templates - Reference docs-codebase for documentation structure
6. Set up automation - Use references/cicd-integration.md for ongoing maintenance

Remember : The goal is not 100% coverage, but useful coverage for the target audience. Document what developers, operators, and integrators actually need.

Fact-Checking

• Use web search/web fetch to verify current external facts, versions, pricing, deadlines, regulations, or platform behavior before final answers.
• Prefer primary sources; report source links and dates for volatile information.
• If web access is unavailable, state the limitation and mark guidance as unverified.

Weekly Installs

65

Repository

vasilyu1983/ai-…s-public

GitHub Stars

49

First Seen

Jan 23, 2026

Security Audits

Gen Agent Trust HubPassSocketPassSnykWarn

Installed on

opencode50

gemini-cli49

cursor49

codex49

github-copilot45

claude-code43