Skip to content
cccskills
FreePublished on GitHub

content-repurposing

Turn public social videos, transcripts, posts, creator research, or the user's own source material into platform-specific LinkedIn posts, X posts and threads, short-form scripts, newsletters, blog outlines, carousel briefs, and content calendars. Use when the user wants to reuse a strong idea without copying the source.

The English summary is being prepared. Showing the original description.

Works withLinkedIn

Run score Not tested

See how to install

Files included (2)

  • SKILL.md3.7 KB
  • skill.meta.json643 B

SKILL.md (original)

Review the instructions the agent will receive before you install.

Content Repurposing

Convert source material into original, voice-matched content for the channels the user actually needs.

Inputs

  • Source URLs, transcripts, posts, research reports, or owned source material.
  • Target audience, brand or company voice, platforms, formats, objective, and desired quantity.
  • Optional Brand Core, voice guide, campaign, offer, CTA, and publishing window.

Workflow

  1. Confirm which sources may be transformed and whether they are owned, quoted, or used only as inspiration.
  2. For a video source, use transcript-intelligence to obtain or analyze its transcript. Do not download, transcode, or edit the video, and do not introduce an FFmpeg dependency. If the user already supplied a transcript or captions, work from them directly. If only a URL is available and the current environment cannot call the transcript provider, ask for the transcript or captions; do not improvise a terminal-only media workflow.
  3. Use outlier-post-finder or creator-profile-teardown when the user wants to repurpose a winning pattern rather than a single source.
  4. Extract content atoms: hooks, stories, claims, proof, frameworks, questions, examples, objections, visuals, and calls to action. Retain the source and support for every factual atom.
  5. Choose only formats that fit the audience and objective. Define the platform constraint, distinct angle, and intended action for each output.
  6. Rewrite from the user's perspective and voice. Use create-linkedin-content and create-x-content for final platform tuning when those formats are requested.
  7. Produce ready-to-edit drafts, not a list of generic ideas. Vary the structure by platform and include attribution notes where a source materially influenced the output.
  8. Self-check for voice, factual support, repetition, plagiarism risk, platform fit, and whether each derivative stands on its own.

Runtime paths

  • Transcript or text supplied: fully terminal-free. Repurpose the supplied material directly.
  • Public video URL with GooseWorks MCP: use transcript-intelligence, then call the managed provider through the live call_data_provider schema. No terminal or separate provider key is required.
  • Public video URL with GooseWorks CLI: use transcript-intelligence and its declared provider dependency, then continue with the transcript.
  • Public video URL without either provider path: explain that the transcript cannot be fetched in this environment and request pasted captions or a transcript.

Output

  • Source inventory and content-atom table.
  • Repurposing map showing source atom, target format, audience, angle, and CTA.
  • Platform-ready drafts grouped by channel.
  • Optional carousel or visual briefs for goose-graphics when requested.
  • Suggested publishing sequence and content calendar when requested.
  • Attribution notes, factual checks, and items requiring user review.

Guardrails

  • Adapt ideas, evidence, and structures; do not plagiarize distinctive language or creative expression.
  • Quote only short, necessary excerpts and retain attribution.
  • Do not flatten every platform into the same draft with a different character count.
  • Do not invent facts, personal experience, customer proof, or first-person claims for the user.
  • Do not require FFmpeg or a local terminal. This skill transforms source meaning into written content; it does not process video files.

Reviews

No reviews yet. Tell others what you thought.

Comments

No login needed. Share how it worked for you, ask a question, or note where it did not run.

No comments yet. Be the first to write one.

Comments are published right away. Do not include personal information such as email addresses or phone numbers. Up to 2 URLs.

0 / 1,000 characters

This form is protected by reCAPTCHA, and the Google Privacy Policy and Terms of Service apply.

More skills from this repository

Research supported advertising promises from a specific buyer's context, current product facts, customer language and observed ads. Turn them into static, video or copy ideas; match video ideas to actual recipes and save a product-scoped angle bank for write-video-ad-script. Product-led discovery can use verified facts without reviews. Reference persistence and reach are observations, not proof of performance.

The English summary is being prepared. Showing the original description.

gooseworks-ai/goose-skills1.3KUpdated Oct 24, 2026

Analyze ad campaign performance data (Google, Meta, LinkedIn) to identify what's working, what's wasting budget, and specific cut/scale/test recommendations. Runs statistical analysis, funnel diagnostics, and multi-channel budget reallocation with specific dollar-amount shift recommendations and scenario modeling.

The English summary is being prepared. Showing the original description.

gooseworks-ai/goose-skills1.3KUpdated Oct 24, 2026

For paid lead-gen and participant-recruitment ads, replaces vanity CPA with true CAC per qualified lead by joining ad-platform data with downstream funnel events, surfaces tracking gaps, and classifies every creative into Scale / Keep / Investigate / Cut.

The English summary is being prepared. Showing the original description.

gooseworks-ai/goose-skills1.3KUpdated Oct 24, 2026

The intake stage of a Meta ad harness. Researches the brand first, states what it assumes, and asks only what it cannot infer and what would change money, claims or legal exposure if guessed wrong — at most four questions a turn, in plain business language. Writes the brand's stable facts (ads/brand.md), the campaign brief, and a log of what was asked vs assumed. Use it when someone wants to run Meta ads and the brand's ad facts are not yet recorded.

The English summary is being prepared. Showing the original description.

gooseworks-ai/goose-skills1.3KUpdated Oct 24, 2026

Checks paid ads against the ad platform's rules (Meta, TikTok, Google, LinkedIn and others) and the brand's category rules: the copy, on-image or on-screen text, pictures and people. Rewrites what can be fixed honestly, adds the disclosures that are needed, and flags anything that needs a human or legal review, with one pass, fixed or flag line per ad and platform. Use alone when you already have the ad text or images and know where they will run; otherwise run the playbook for the job (e.g. make-static-ads, make-content, email-lifecycle).

The English summary is being prepared. Showing the original description.

gooseworks-ai/goose-skills1.3KUpdated Oct 24, 2026

Analyze the message match between your ads and landing pages. Checks if the promise in the ad copy carries through to the landing page headline, body, and CTA. Flags disconnects that kill conversion rates. Works with Google, Meta, and LinkedIn ads.

The English summary is being prepared. Showing the original description.

gooseworks-ai/goose-skills1.3KUpdated Oct 24, 2026

See all skills by gooseworks-ai

Report a problem with this skill