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Content Research

skill-ootto-ai-claude-content-skills-content-research · by Ootto-AI

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Install

$ agentstack add skill-ootto-ai-claude-content-skills-content-research

✓ scanned · ✓ verified — works with Claude Code, Cursor, and more.

Security review

✓ Passed

No issues found. Passed automated security review. · v0.1.0 How review works →

  • Prompt-injection patterns
  • Secret / credential exfiltration
  • Dangerous shell & filesystem operations
  • Untrusted network calls
  • Known-malicious package signatures

What it can access

  • Network access No
  • Filesystem access No
  • Shell / process execution No
  • Environment & secrets No
  • Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

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About

Content Research — stop guessing what to post

Most people spend hours scrolling to figure out what to post. This skill turns Claude into a research machine: point it at any account or niche and it finds the exact moments that went viral and the patterns behind them — so you copy what works instead of guessing.

What it does

  1. Pull the posts. For a creator/account, gather their recent reels + view counts (Instagram Graph

API via Composio, or any list of reel URLs the user provides).

  1. Find the spikes. Rank posts by views and flag the outliers — the exact posts where the account

blew up vs their baseline. Those are the moments worth studying.

  1. Break down WHY. For each outlier, study the reel frame-by-frame + transcript (hand off to the

reel-analyzer skill / ootto-watch) and extract the hook (first 2s), the format/structure, the pacing, and the retention pattern.

  1. Surface the playbook. Across the outliers, surface the repeatable patterns — the hook types,

formats, and topics that consistently earn saves/shares — and turn them into a short, copyable plan for the user's own niche.

How to run it

  1. Ask for a creator @handle, an account URL, or a niche (+ a few example accounts).
  2. Pull their reels + view counts. Options:
  • sandcastles.ai — a research engine that pulls top channels and auto-surfaces the viral outliers + the

frameworks behind them (fastest path; connect it to Claude and let it do the heavy lifting).

  • Composio Instagram tools — free/DIY: list a creator's media + insights from the Graph API.
  • Or a plain list of reel URLs the user pastes.
  1. Rank by views, compute each post's ratio vs the account median, and mark anything ~2-3x median as an

outlier ("blew up here").

  1. For the top 3-5 outliers, run reel-analyzer (or ootto-watch — github.com/Ootto-AI/ootto-watch) to

break down hook / format / retention.

  1. Synthesize: list the winning hook patterns, formats, and topics, then write 3 ready-to-shoot ideas for

the user's own account modeled on what actually worked.

Output

A short research report:

  • The spikes — which posts blew up and by how much (vs baseline).
  • Why they worked — hook / format / retention breakdown per outlier.
  • The playbook — the repeatable patterns + 3 original ideas for your niche.

Honesty

Model the technique, never copy another creator's exact script, visuals, or caption. Cite the source reels you studied. View counts come from real data (Composio / what the user provides) — never fabricate.

Part of the Ootto content-skills marketplace. Pairs with reel-analyzer, going-viral, and reel-scripter.

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

Reviews

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Versions

  • v0.1.0 Imported from the upstream source.