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 Ootto-AI/claude-content-skills --skill content-auditgit clone --depth 1 https://github.com/Ootto-AI/claude-content-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/ootto-ai/claude-content-skills/content-audit)<a href="https://agentmods.dev/skills/ootto-ai/claude-content-skills/content-audit"><img src="https://agentmods.dev/badge/skills/ootto-ai/claude-content-skills/content-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/ootto-ai/claude-content-skills/content-audit"><img src="https://agentmods.dev/badge/skills/ootto-ai/claude-content-skills/content-audit.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00063 | $0.00491 |
| Opus 5 | $0.00032 | $0.00246 |
| Sonnet 5 | $0.00013 | $0.00098 |
| Haiku 4.5 | $0.00006 | $0.00049 |
Grade A, and why
content-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.
What it actually says
Content Audit — what to double down on, and what to stop
Reviews your last 30 posts to find what is worth doubling down on, what is dead weight, and the gaps to fill.
When to use
Before making more, work out what to stop.
What you'll need
Your last 30 posts with views, saves, comments and shares. The Ootto MCP or your Instagram insights export.
Instructions
Give Claude the input and run this.
You are my content analyst. Here are my last 30 posts with their numbers: [paste].
1. MEDIAN FIRST: state my median views/saves so everything is judged against ME, not someone else.
2. OUTLIERS: the posts that beat it, and the trait they share.
3. DEAD WEIGHT: formats or topics I keep making that consistently underperform. Name them plainly.
4. BY TRAIT: score hook style, length, format and topic, each with its real multiple vs median.
5. STOP / KEEP / TEST: three short lists.
6. NEXT FIVE: five posts to make, each justified by a number above.
If a pattern isn't in the data, say "not enough signal" rather than guessing.
Honesty: Every multiple must come from the numbers pasted in. No estimated figures, and no advice that contradicts my own data.
Next: content-pillar-builder → content-calendar
Built by Ootto — the AI autopilot that connects your tools once and runs the busywork for you, automatically. Book a demo →
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 · 53 lines · 63 tokens per session scan A d18379b193f9
content-audit is a skill published in the GitHub repository Ootto-AI/claude-content-skills (28 stars, last pushed 19d ago), licensed MIT. It adds 63 tokens to every session and 491 once invoked, about $0.0003 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 2026-08-30.
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comment-mining
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transcript-intelligence
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