Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add joaquimscosta/arkhe-claude-plugins --skill doc-freshnessgit clone --depth 1 https://github.com/joaquimscosta/arkhe-claude-pluginsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/joaquimscosta/arkhe-claude-plugins/doc-freshness)<a href="https://agentmods.dev/skills/joaquimscosta/arkhe-claude-plugins/doc-freshness"><img src="https://agentmods.dev/badge/skills/joaquimscosta/arkhe-claude-plugins/doc-freshness/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/joaquimscosta/arkhe-claude-plugins/doc-freshness"><img src="https://agentmods.dev/badge/skills/joaquimscosta/arkhe-claude-plugins/doc-freshness.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00107 | $0.01765 |
| Opus 5.5 | $0.00043 | $0.00706 |
| Sonnet 5.5 | $0.00021 | $0.00353 |
| Haiku 4.5 | $0.00011 | $0.00177 |
Grade A, and why
doc-freshness scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured today.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 186 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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.
What ships with it
9 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- EXAMPLES.md 10 KB
- scripts/claude_md_checker.py 17 KB runs code
- scripts/frontmatter_onboard.py 7.8 KB runs code
- scripts/link_checker.py 6.0 KB runs code
- scripts/scan_freshness.py 12 KB runs code
- scripts/shared.py 18 KB runs code
- scripts/version_checker.py 14 KB runs code
- TROUBLESHOOTING.md 3.5 KB
- WORKFLOW.md 13 KB
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- today First seen · 186 lines · 107 tokens per session scan A 33493ccb0134
doc-freshness is a skill published in the GitHub repository joaquimscosta/arkhe-claude-plugins (21 stars, last pushed today), licensed MIT. It adds 107 tokens to every session and 1,765 once invoked, about $0.0004 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-10-16.
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