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 JakeLabate/Claude-SEO-Skills --skill content-quality-auditgit clone --depth 1 https://github.com/JakeLabate/Claude-SEO-SkillsWrote 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/jakelabate/claude-seo-skills/content-quality-audit)<a href="https://agentmods.dev/skills/jakelabate/claude-seo-skills/content-quality-audit"><img src="https://agentmods.dev/badge/skills/jakelabate/claude-seo-skills/content-quality-audit/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/jakelabate/claude-seo-skills/content-quality-audit"><img src="https://agentmods.dev/badge/skills/jakelabate/claude-seo-skills/content-quality-audit.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 | $0.00115 | $0.01237 |
| Opus 5 | $0.00057 | $0.00619 |
| Sonnet 5 | $0.00023 | $0.00247 |
| Haiku 4.5 | $0.00012 | $0.00124 |
Grade A, and why
content-quality-audit 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 11d ago.
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 — 112 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Content Quality Audit
Audit a website's content for thinness and duplication, and produce an actionable report. These checks surface pages unlikely to rank or add value; they are signals for human review, calibrated to the site.
When to use this skill
Use this skill when the user asks to:
- Audit or fix thin / low-value content
- Find duplicate or near-duplicate pages (templated/boilerplate content)
- Check content depth or text-to-HTML ratio
- Identify doorway-style pages
Inputs to collect
- Site URL or URL list — a live site root to crawl (auto-seeds from
/sitemap.xml), or a text file with--url-list. - Scope — pages to crawl (default 500,
--max-pages). - Thresholds —
--thin-words(default 300) and--similarity(default 0.85). Calibrate to the content type before running.
Workflow
Step 1: Crawl and measure content
Use scripts/extract_content.py:
python3 scripts/extract_content.py https://example.com --max-pages 500 --output content_inventory.json
# already crawled once (e.g. in a full SEO audit)? skip the crawl and reuse the shared cache:
# python3 scripts/fetch_pages.py https://example.com --output page_cache.json
# python3 scripts/extract_content.py --from-cache page_cache.json --output content_inventory.json
For each page it records visible word count, text-to-HTML ratio, title, H1, noindex, an exact content hash, and a 32-value MinHash signature for fast near-duplicate detection.
Step 2: Run the audit checks
python3 scripts/audit_content.py content_inventory.json --thin-words 300 --similarity 0.85 --output audit_report.json
Step 3: Evaluate the audit checks
Evaluate each check in references/audit-checks.md. Core checks:
| Check | Severity |
|---|---|
| Thin content (below word threshold) | High |
| Duplicate content (identical body) | High |
| Near-duplicate content (high MinHash similarity) | Medium |
| Low text-to-HTML ratio | Medium |
| Missing H1 | Low |
Step 4: Produce the report
What ships with it
7 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.
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.
- 11d ago First seen · 112 lines · 115 tokens per session scan A 9e557228fdcf
content-quality-audit is a skill published in the GitHub repository JakeLabate/Claude-SEO-Skills (2 stars, last pushed 2mo ago), licensed MIT. It adds 115 tokens to every session and 1,237 once invoked, about $0.0006 per session on Opus 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 2026-08-31.
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