content-audit

content-audit is a skill for Claude Code from Ootto-AI/claude-content-skills. It costs 63 tokens per session (491 once invoked), scanned A, original, MIT.

A review of the last 30 social-media posts using their views, saves, comments, and shares. It compares results with the account's own typical performance.

In plain words
What is it for?
Use it to find posts that beat the median, assess hooks, lengths, formats, and topics, decide what to stop or continue, and choose the next five posts.
Why use it?
It helps separate repeatable patterns from isolated successes and identifies topics or formats that consistently underperform without guessing when the data is insufficient.

Skill for Claude Code

Written for Claude Code: argument-hint in frontmatter.

Part of the claude-content-skills plugin — 52 skills shipped together

Good fit Use it to find posts that beat the median, assess hooks, lengths, formats, and topics, decide what to stop or continue, and choose the next five posts.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/ootto-ai/claude-content-skills/content-audit
Install

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.

Any agent
npx skills add Ootto-AI/claude-content-skills --skill content-audit
Clone the repo
git clone --depth 1 https://github.com/Ootto-AI/claude-content-skills

Made for: Claude Code.

Or install claude-content-skills, the plugin that ships this one along with the rest of its 52 skills.

Wrote 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.

agentmods badge for content-audit

README.md
[![agentmods](https://agentmods.dev/badge/skills/ootto-ai/claude-content-skills/content-audit/github.svg)](https://agentmods.dev/skills/ootto-ai/claude-content-skills/content-audit)
Your own site
<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.

agentmods 80×15 button for content-audit

Your own site · 80×15
<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>
Per session 63 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 491 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce 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

Measured 11d ago against content hash d18379b193f9, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

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.

skills/content-audit/SKILL.md · 53 lines

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-buildercontent-calendar


Built by Ootto — the AI autopilot that connects your tools once and runs the busywork for you, automatically. Book a demo →

Changes

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.

  1. 11d ago First seen · 53 lines · 63 tokens per session scan A d18379b193f9

Subscribe to this mod's changes

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.

Related

Other skills, from other repositories

scrapecreators-api

Scrape and extract public data from 27+ social media platforms using the ScrapeCreators REST API. Covers TikTok, Instagram, YouTube, LinkedIn, Facebook, Twitter/X, Reddit, Threads, Bluesky, Pinterest, Snapchat, Twitch, Kick, Truth Social, TikTok Shop, Google, and link-in-bio services (Linktree, Komi, Pillar, Linkbio…

ScrapeCreators/social-media-research-skills · 161 tokens

outlier-post-finder

Use when the user wants to find posts, videos, reels, shorts, tweets, or social content that overperformed versus a creator, brand, or competitor baseline. Finds outliers, explains why they worked, extracts hooks and formats, and produces a practical swipe file.

ScrapeCreators/social-media-research-skills · 60 tokens

competitor-social-research

Use when the user wants to research competitors' social media strategy, compare brands or creators, find what content is working in a niche, identify content gaps, or produce a practical social strategy brief from public social data.

ScrapeCreators/social-media-research-skills · 49 tokens

ad-library-teardown

Use when the user wants to analyze active ads from Meta/Facebook, Google, or LinkedIn ad libraries; tear down a competitor's messaging; extract hooks, offers, CTAs, video transcripts, landing page claims, and test ideas from public ads.

ScrapeCreators/social-media-research-skills · 56 tokens

comment-mining

Use when the user wants to mine comments and replies for audience reactions, customer language, questions, objections, complaints, product ideas, buying intent, sentiment, or voice-of-customer insights from public social posts and videos.

ScrapeCreators/social-media-research-skills · 48 tokens

transcript-intelligence

Use when the user wants to summarize, analyze, or repurpose transcripts from TikTok, Instagram, YouTube, Facebook, X/Twitter, LinkedIn, Rumble, or Reddit video posts. Extracts hooks, claims, quotes, content atoms, themes, and reusable scripts.

ScrapeCreators/social-media-research-skills · 62 tokens