Skill

doc-freshness

Detect documentation drift, stale references, and cross-document inconsistencies in any project. Scans for code-doc drift (API/function changes not reflected in docs), cross-doc drift (conflicting information across documents), and stale references (broken links, deleted files, outdated versions). Use when checking "doc freshness", "stale docs", "documentation drift", "broken links", "outdated documentation", "doc accuracy", "docs out of date", "doc audit", "doc health", or "verify documentation".

From roadmap

Install

Run in your terminal

npx claudepluginhub joaquimscosta/arkhe-claude-plugins --plugin roadmap

Tool Access

This skill is limited to using the following tools:

ReadGlobGrepBashWrite

Supporting Assets

View in Repository

EXAMPLES.md

TROUBLESHOOTING.md

WORKFLOW.md

scripts/link_checker.py

scripts/scan_freshness.py

scripts/shared.py

scripts/version_checker.py

Skill Content

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 roadmap: section for output_dir (used by report mode, default: arkhe/roadmap).

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}/freshness/`
(none)	Full scan (same as `scan`)

Mode Execution

`scan` (default)

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

`links`

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

`check <path>`

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

`drift <path>`

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

`cross-doc`

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

`report`

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

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

Similar Skills

cache-components

Expert guidance for Next.js Cache Components and Partial Prerendering (PPR). **PROACTIVE ACTIVATION**: Use this skill automatically when working in Next.js projects that have `cacheComponents: true` in their next.config.ts/next.config.js. When this config is detected, proactively apply Cache Components patterns and best practices to all React Server Component implementations. **DETECTION**: At the start of a session in a Next.js project, check for `cacheComponents: true` in next.config. If enabled, this skill's patterns should guide all component authoring, data fetching, and caching decisions. **USE CASES**: Implementing 'use cache' directive, configuring cache lifetimes with cacheLife(), tagging cached data with cacheTag(), invalidating caches with updateTag()/revalidateTag(), optimizing static vs dynamic content boundaries, debugging cache issues, and reviewing Cache Component implementations.

138.5k

brand-guidelines

1 file

Applies Anthropic's official brand colors and typography to any sort of artifact that may benefit from having Anthropic's look-and-feel. Use it when brand colors or style guidelines, visual formatting, or company design standards apply.

99.3k

algorithmic-art

3 files

Creating algorithmic art using p5.js with seeded randomness and interactive parameter exploration. Use this when users request creating art using code, generative art, algorithmic art, flow fields, or particle systems. Create original algorithmic art rather than copying existing artists' work to avoid copyright violations.

99.3k

Stats

Parent Repo Stars9

Parent Repo Forks1

Last CommitMar 22, 2026

Actions

View Source View Plugin View on GitHub View README