kai-repurpose

name

kai-repurpose

description

Take one pillar content piece and produce 15-25 derivative assets across platforms — social posts, email, LinkedIn article, video scripts, newsletter section, infographic brief, and more. The ultimate content multiplier. Use when "repurpose this", "turn this into", "make social posts from this blog", "content repurposing", "1 to many", "atomize this content", "extract posts from", or any request to derive multiple pieces from one source.

Kai root note: knowledge/, harness/, and scripts/ paths in this skill live in the Kai install, not the user's project. Resolve them against the first ancestor directory of this SKILL.md that contains a knowledge/ folder (the Kai plugin root, ~/.claude/kai, or the kai-cmo-harness repo). MARKETING.md, memory/, and any output files live in the current project. If a referenced scripts/ command is not available in this install, say so, skip it, and continue with the file-based guidance — never fabricate its output.

Take 1 pillar → produce 15-25 channel-specific assets. The content multiplier.

Phase 0: Load Product Context

Check if MARKETING.md exists in the project root (same directory as CLAUDE.md, README.md, package.json).

If it exists: Read it — skip product discovery questions. It has the product name, ICP, value prop, monetization, brand voice, current channels, and competitive landscape.

If it does NOT exist: Auto-explore the codebase to create it in the project root (next to CLAUDE.md). Do NOT ask the user what the product is. Read CLAUDE.md, README.md, PROJECT.md, package.json, landing pages, and any project files. Search for email/ad/analytics config. Then create MARKETING.md using the template from /kai-email-system. Present draft to user for confirmation.

---

Phase 1: Pillar Input

Read from MARKETING.md. Only ask about things not covered there:

1. Source content — paste it, link it, or point to the file
2. Platforms — which channels should get derivative content?
3. Priority — what matters most? (social reach, email engagement, SEO, video views)

Load: knowledge/playbooks/content-repurposing.md

Phase 2: Extraction Map

Read the pillar content and extract:

• Key insights (3-5 standalone ideas)
• Data points (stats, numbers, results)
• Quotable lines (bold claims, memorable phrases)
• Steps/frameworks (any process or list)
• Stories/examples (anecdotes, case studies)
• Contrarian takes (anything that challenges conventional wisdom)

Generate workspace/repurposed/_extraction-map.md:

Extract	Type	Best Channel	Format
"Stat about X"	Data point	X, LinkedIn	Single post
"3-step framework"	Process	Instagram carousel, LinkedIn	Carousel / text post
"Contrarian claim"	Take	X thread, TikTok	Thread / video script
...	...	...	...

Quote Mining Pass

When the source is a transcript, podcast, webinar, interview, or long article, run a quote mining pass before derivative production.

Load harness/references/transcript-video-research-rules.md before quote mining third-party video, audio, podcast, webinar, or transcript material.

Create workspace/repurposed/_quote-bank.md with:

• Source location: file path, URL, episode name, transcript timestamp, or paragraph locator
• Quote or paraphrase: mark direct quotes clearly; keep direct quotes short
• Use case: hook, proof, objection, story, CTA, email subject, clip candidate
• Risk note: unsupported claim, private detail, medical/legal/financial claim, or needs approval
• Attribution requirement: guest name, customer approval, anonymous/internal, or source citation

Rules:

• Preserve exact source locations so every derivative can be traced back.
• Do not invent quotes, credentials, or expert authority.
• Treat quote mining as source extraction, not rewriting. Rewrite only in derivative files.
• Draft as a dry run first; publishing or scheduling requires explicit approval.

Phase 3: Derivative Production

From one pillar, produce:

Standard Derivative Set (adapt based on platforms)

#	Asset	Platform	Format
1	LinkedIn text post (insight #1)	LinkedIn	1200 chars
2	LinkedIn text post (insight #2)	LinkedIn	1200 chars
3	LinkedIn carousel (framework)	LinkedIn	8-10 slides outline
4	X/Twitter thread (full argument)	X	5-7 tweets
5	X/Twitter single tweet (data point #1)	X	280 chars
6	X/Twitter single tweet (data point #2)	X	280 chars
7	X/Twitter single tweet (contrarian take)	X	280 chars
8	Instagram carousel (key takeaways)	Instagram	5-7 slides outline
9	Instagram caption (story/example)	Instagram	150-300 words
10	TikTok video script (hook + insight)	TikTok	30-60 seconds
11	TikTok video script (contrarian take)	TikTok	15-30 seconds
12	Email newsletter section	Email	100-200 words
13	Email standalone (value-add)	Email	300-500 words
14	LinkedIn article (expanded angle)	LinkedIn	2,200-3,000 words
15	YouTube Shorts script	YouTube	30-60 seconds
16-25	Additional platform-specific variants	Various	Various

Rules

• Each derivative must stand alone (no "as I wrote in my blog post...")
• Adapt tone to platform (LinkedIn = professional, X = punchy, TikTok = conversational)
• Different hook for each piece (even when based on the same insight)
• Every piece gets quality gate check: zero banned words, zero AI slop, platform limits
• Credit the pillar only if the platform norms expect it

Phase 4: Output

workspace/repurposed/
├── _extraction-map.md
├── _source-pillar.md          # Copy of original for reference
├── linkedin/
│   ├── post-insight-1.md
│   ├── post-insight-2.md
│   ├── carousel-framework.md
│   └── article-expanded.md
├── x-twitter/
│   ├── thread-full.md
│   ├── tweet-stat-1.md
│   ├── tweet-stat-2.md
│   └── tweet-contrarian.md
├── instagram/
│   ├── carousel-takeaways.md
│   └── caption-story.md
├── tiktok/
│   ├── script-insight.md
│   └── script-contrarian.md
├── email/
│   ├── newsletter-section.md
│   └── standalone-email.md
├── youtube/
│   └── shorts-script.md
└── _quality-report.md

Phase 5: Publishing Schedule

Generate a suggested posting schedule — stagger derivatives over 1-2 weeks so they don't cannibalize each other. Lead with the highest-reach platform, follow with niche channels.