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SKILL verified MIT Self-run

Podcast To Clips

skill-gokulb20-crewm8-social-media-manager-skill-graph-podcast-to-clips · by gokulb20

Extract podcast episode transcripts into quote tweets, Instagram Reels copy, LinkedIn highlight posts, and TikTok script hooks — turning 60-minute conversations into 5-8 social assets.

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Install

$ agentstack add skill-gokulb20-crewm8-social-media-manager-skill-graph-podcast-to-clips

✓ 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.

View the full security report →

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Reliability & compatibility

Security review passed
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Declared compatibility

Claude CodeClaude Desktop

Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.

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About

Podcast to Clips

Distill podcast and video interview transcripts into platform-native social assets. A single 60-minute episode should yield 5-8 posts across platforms, not just one "new episode out" announcement.

Purpose

Podcasts are a content goldmine that most brands under-leverage. Each episode contains 5-8 moments worth posting. This skill extracts them, formats them per platform, and sequences the clips so one episode feeds a week of content.

When to Use

  • New podcast episode published
  • Founder was a guest on someone else's podcast
  • Older episode that performed well deserves a second push
  • Building a clips library for ongoing content

Inputs Required

  • Full podcast transcript (auto-generated is fine)
  • Episode title, host/guest handles, episode URL
  • Brand voice guide
  • Any specific clips the founder wants to highlight

Quick Reference

| Podcast Segment | Best Clip Format | Best Platform | |----------------|-----------------|--------------| | Hot take / contrarian opinion | Quote tweet or text-over-video | X, TikTok | | Data point or surprising stat | Quote card + stat-led post | X, LinkedIn | | Personal story | Video clip (30-60s) + caption | IG, TikTok | | Framework or system | Carousel or thread | LinkedIn, X | | Practical tip / how-to | Short video (15-30s) or text post | TikTok, IG, X |

Procedure

  1. Read the full transcript. Timestamp every moment that:
  • Made you pause or think differently
  • Contained a specific number or data point
  • Told a concrete story
  • Stated something contrarian or controversial
  • Offered a framework or step-by-step process
  • Was genuinely funny or human
  1. For each timestamped moment, determine the best format:
  • Quote tweet: exact quote + 1-2 lines of context
  • Video clip: exact time range (15-90 seconds), text overlay hook
  • Carousel/post: if it's a framework, draft slide structure
  • Thread: if connected insights, build 3-5 tweet mini-thread
  1. For video clips:
  • Clip length: 15-30s for TikTok/Reels, 30-90s for X, 60s max for LinkedIn
  • Include captions/subtitles
  • Write text overlay hook for first 1.5 seconds
  • Write platform-native caption
  1. For each clip, draft: hook, caption/body text, CTA, hashtags.
  1. Organize clips into a posting schedule:
  • Best clip first (within 24h of episode drop)
  • Spread remaining clips across 5-7 days
  • Do not post all clips the same day
  1. Include attribution. Tag the host's account (if guesting). Link to full episode in every clip's caption or final tweet.

Output Format

# Podcast Clips: [Episode Title]

## Source
[Episode link + timestamp]

## Clip Inventory

### Clip 1: [Topic]
**Timestamp:** [MM:SS - MM:SS]
**Format:** [Video clip / Quote tweet / Thread / Carousel]
**Platform:** [Primary + secondary]
**Hook / Text overlay:** [Text]
**Caption / Body:** [Full text]
**CTA:** [CTA]
**Hashtags:** [Platform-appropriate set]

### Clip 2...
...

## Posting Schedule
- Day 1: [Clip X on platform Y]
- Day 2: [Clip X on platform Y]
...

Done Criteria

The skill is complete when:

  1. At least 5 clips are extracted per 60-minute episode
  2. Each clip has a timestamp, format, platform assignment, and caption
  3. Video clips specify time ranges and text overlay hooks
  4. A posting schedule spaces clips across at least 5 days
  5. All clips include attribution links

Pitfalls

  • Clips the host finds interesting but the audience doesn't
  • Video clips without captions/subtitles (unwatchable for most consumption)
  • Posting all clips at once (floods feed, reduces per-clip engagement)
  • Same caption for every clip ("new episode out!") instead of clip-specific hooks
  • Clips that require full-episode context to make sense

Verification

For each clip: if you saw this in your feed without knowing the podcast, would it make sense? If the hook is "new episode" — rewrite to a content-first hook.

Example

Input: 60-minute podcast episode. Founder guests on "The B2B Growth Show." Topic: cold outreach strategies.

Extracted clips:

  1. (Quote tweet) Timestamp 12:30 — "Most cold outreach is lazy, it's not broken." Format: quote tweet. Platform: X.
  2. (Framework) Timestamp 24:00 — "The 3-question qualification framework." Format: carousel. Platform: LinkedIn.
  3. (Story) Timestamp 38:00 — "How one cold email led to a $50K deal." Format: video clip (45s). Platform: IG + TikTok.
  4. (Data point) Timestamp 51:00 — "Open rates dropped 40% when we made this one change." Format: stat-led post. Platform: X.
  5. (Tip) Timestamp 55:00 — "The exact DM template that books meetings." Format: short video (20s). Platform: TikTok.

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.

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Versions

  • v0.1.0 Imported from the upstream source.