Social Media Research Skills is a collection of workflows that let AI coding agents research public social-media data across platforms such as TikTok, Instagram, YouTube, Reddit, and LinkedIn. Marketers and researchers use it to find unusually successful posts, mine comments, study competitors, analyze ads, and extract trends into business outputs. The catalogue skills and plugin package these workflows for supported AI agents.
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 ScrapeCreators/social-media-research-skills --skill transcript-intelligencegit clone --depth 1 https://github.com/ScrapeCreators/social-media-research-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/scrapecreators/social-media-research-skills/transcript-intelligence)<a href="https://agentmods.dev/skills/scrapecreators/social-media-research-skills/transcript-intelligence"><img src="https://agentmods.dev/badge/skills/scrapecreators/social-media-research-skills/transcript-intelligence/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/scrapecreators/social-media-research-skills/transcript-intelligence"><img src="https://agentmods.dev/badge/skills/scrapecreators/social-media-research-skills/transcript-intelligence.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk warn
- 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 | $0.00062 | $0.00905 |
| Opus 5.5 | $0.00025 | $0.00362 |
| Sonnet 5.5 | $0.00012 | $0.00181 |
| Haiku 4.5 | $0.00006 | $0.00090 |
Grade A, and why
transcript-intelligence 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 1mo 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 — 132 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Transcript Intelligence
Overview
Turn public video transcripts into useful research and content assets. This skill is for extracting signal from spoken social video: hooks, claims, stories, objections, examples, CTAs, and reusable content angles.
When to Use
Use this skill when the user asks to:
- summarize a video, reel, short, TikTok, podcast clip, or social video
- analyze a creator's hooks or speaking style
- extract quotes, claims, examples, and CTAs from transcripts
- turn transcripts into social posts, scripts, newsletters, or content ideas
- compare what multiple creators say about a topic
Transcript Sources
| Platform | Endpoint |
|---|---|
| TikTok | /v1/tiktok/video/transcript |
/v2/instagram/media/transcript |
|
| YouTube | /v1/youtube/video/transcript, /v1/youtube/video |
/v1/facebook/post/transcript |
|
| X/Twitter | /v1/twitter/tweet/transcript |
/v1/linkedin/post/transcript |
|
| Rumble | /v1/rumble/video/transcript |
| Reddit video | /v1/reddit/post/transcript |
If a detail endpoint already includes transcript text, use it. If transcript is unavailable, say so and fall back to title/caption/description only.
Workflow
-
Collect URLs or discover videos
- If URLs are provided, fetch each transcript directly.
- If a creator/channel is provided, first fetch recent posts/videos, then choose relevant videos.
-
Extract transcript text
- Preserve timestamps if provided.
- Keep source URL with each transcript.
- Do not hallucinate missing captions.
-
Segment the transcript Break into:
- hook/opening
- setup/context
- main claim or lesson
- evidence/examples
- payoff
- CTA
-
Analyze the content Extract:
- exact hooks
- claims and contrarian takes
- stories
- frameworks
- objections addressed
- emotional language
- quotable lines
- content atoms that stand alone
-
Synthesize across multiple transcripts
- Cluster by topic and angle.
- Count recurring themes.
- Identify repeated hook formulas.
- Flag the strongest examples with citations.
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.
- 1mo ago First seen · 132 lines · 62 tokens per session scan A 599e19d53de3
transcript-intelligence is a skill published in the GitHub repository ScrapeCreators/social-media-research-skills (4,948 stars, last pushed 2mo ago), licensed MIT. It adds 62 tokens to every session and 905 once invoked, about $0.0002 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 2026-08-30.
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