doc-freshness

Documentation Freshness

Detect documentation drift across any project. Reports findings without auto-fixing.

Context Discovery

Priority 1: Configuration

Read .arkhe.yaml from project root. Extract doc-freshness: section for custom patterns, exclusions, and doc-code mappings. Extract doc-health: section for output_dir (used by report mode, default: docs/health).

Priority 2: Project Identity

Read CLAUDE.md and README.md to understand project structure, tech stack, and conventions.

Priority 3: Documentation Inventory

Run the scanner to discover all documentation files and perform mechanical checks:

python3 ${CLAUDE_SKILL_DIR}/scripts/scan_freshness.py <project-root>

Use --links-only for fast mode (links and file refs only, no git staleness).

Arguments

Parse from $ARGUMENTS:

Mode	Description
scan	Full freshness analysis (all three drift types)
check <path>	Focused analysis on one file or directory
links	Broken links and stale references only (script-driven, fast)
drift <path>	Code-doc drift for a specific doc or doc-code pair
cross-doc	Cross-document consistency check
report	Persist structured freshness report to {output_dir}/
claude-md	CLAUDE.md structural drift (plugin counts, components, versions)
onboard	Suggest/apply tracking frontmatter to docs that need it
setup	Scaffold GitHub Actions workflow for docs-health-action CI
(none)	Full scan (same as scan)

Scanning Tiers

Documents are automatically classified into scanning tiers:

Tier	Detection	Checks Performed
Basic	All .md files	Broken links, git age classification, backtick-path verification
Deep	YAML frontmatter with last_updated or version	Basic + version drift, last_updated accuracy, cross-doc consistency

Tier is auto-detected per file. No configuration needed. The scanner JSON output includes "tier" per doc and "tier_counts" in the summary.

Mode Execution

scan (default)

1. Run scan_freshness.py for mechanical checks (links, versions, git staleness)
2. Present script findings (broken links table, version mismatches, staleness scores)
3. For stale/very_stale docs: use Grep/Read to check code-doc alignment on key references
4. For docs covering the same topic: cross-check for consistency
5. Produce the freshness report

links

1. Run scan_freshness.py --links-only
2. Present broken links table directly from JSON output
3. Group findings by severity: broken links first, then file_ref warnings

check <path>

1. If path is a file, run link checker and version checker on that file only
2. If path is a directory, scan all .md files within it
3. Use Grep to check file path references and function names against the codebase
4. Report findings for the targeted scope

drift <path>

1. Read the specified doc
2. Extract: function/method names, API endpoints, file paths, config keys, class names
3. Grep/Read the corresponding code to verify each reference still exists and is accurate
4. Report mismatches with evidence (doc line vs code location)

cross-doc

1. Run scan_freshness.py to get doc inventory with headings
2. Identify docs with overlapping topics (shared heading keywords)
3. Read overlapping docs and compare factual claims
4. Flag contradictions (e.g., different version requirements, conflicting setup steps)

report

Same as scan but write output to {output_dir}/{YYYY-MM-DD}-freshness.md.

claude-md

1. Run claude_md_checker.py to compare CLAUDE.md claims against filesystem
2. Present findings by category: plugin counts, component inventories, versions, file paths
3. Highlight undocumented components (CRITICAL) and version mismatches (WARNING)

onboard

1. Run frontmatter_onboard.py to find docs without tracking frontmatter
2. Uses whitelist of known-maintained docs (READMEs, custom docs)
3. Generates minimal title + last_updated frontmatter from git history
4. On user approval, apply with --apply flag

setup

Scaffold a GitHub Actions workflow that runs joaquimscosta/docs-health-action@v1 on every PR.

1. Check if .github/workflows/ exists — create if needed
2. Check if a docs-health workflow already exists — warn and offer to overwrite/skip
3. Ask user which checks to enable (use AskUserQuestion with multiSelect):
   • links (broken internal links and anchors)
   • versions (version references vs ground truth files)
   • staleness (git-based documentation age)
   • claude-md (CLAUDE.md structural drift — Claude Code projects only)
   • cross-doc (cross-document version conflicts)
   • frontmatter (missing tracking frontmatter)
4. Ask user for failure policy: errors (default), warnings, or none (advisory)
5. Generate .github/workflows/docs-health.yml from template
6. Show the generated file and confirm before writing

See WORKFLOW.md § setup for the full template.

Automation Integration

SessionStart Hook: Critical-doc fast scan on session start (5-second timeout)

/doc:health --critical-only
# Scans: README.md, CLAUDE.md only (root-level critical docs)

PostToolUse Hook (after /commit): Post-commit doc-impact checks

/doc:health drift
# Checks if modified code files have corresponding documentation

User-Driven (/loop): Periodic freshness monitoring

/loop 1h /doc:health links        # Hourly broken-link checks
/loop 4h /doc:health scan         # Full scans every 4 hours

Severity Levels

Severity	Meaning
CRITICAL	Broken link to deleted file, doc references removed API/function
WARNING	Version mismatch, function signature changed, doc stale >30 days
INFO	Minor inconsistency, doc aging (7-30 days), cosmetic drift

Output Rules

• Evidence-based: every finding backed by file path and line number
• Tabular: summary table first, detailed findings below
• Actionable: each finding includes what needs updating
• Detection only: NEVER auto-fix documentation

Lane Discipline

• Do NOT update or rewrite documentation — detection only
• Do NOT produce roadmap status, architecture analysis, or user stories
• Do NOT write source code

References

• WORKFLOW.md — Detection algorithms and convention tables
• EXAMPLES.md — Usage examples for each mode
• TROUBLESHOOTING.md — Common issues and fixes