Content repurposer

Skill ARCASSystems/FounderOS/skills/content-repurposer

Reformat one piece of content across many channels. Trigger on "repurpose this", "turn this into", "adapt this for", "convert this to", "make versions of this for", or any variation. Also fires when the user shares content and wants it reformatted for different platforms. Works across LinkedIn, YouTube, Instagram, email newsletters, website copy, Twitter/X, and internal docs. Reads `core/voice-profile.yml` and applies the founder's voice.From its SKILL.md

Install

npx -y skills add ARCASSystems/FounderOS --skill content-repurposer

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

One thing to look at

5 stars5 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

SKILL.md

5.8 KB, as published. Nobody here has run it

Content Repurposer

Runs on: reasoning - reads your files and reasons; any capable agent can run this.

Apply the voice and writing rules from core/identity.md, rules/writing-style.md, and core/voice-profile.yml (via the your-voice skill) to all output. Keep the founder's voice consistent across every channel.

Voice routing (operator or brand?)

Before any gate or draft, apply the routing rules in skills/your-voice/SKILL.md "Voice routing - operator or brand?" section.

Default to operator voice from core/voice-profile.yml.
If the user named a brand they run, or if the source content is brand-owned, use brand voice from brands/<slug>/voice.yml.
For multi-channel repurposing, the SAME voice applies to every channel adaptation. Do not mix voices across the output.

If brands/ does not exist or has no entries, this section is a no-op.

Voice profile readiness

If using operator voice, run: python scripts/check-voice-ready.py

If using brand voice, run: python scripts/check-brand-voice-ready.py --brand <slug>

If exit code is 1, read the output line and surface it to the user verbatim. Do not produce any draft. Stop.

If the user explicitly chooses to proceed with defaults after seeing that message, repurpose the content using the universal anti-AI baseline from your-voice and clearly label that the voice profile was not applied. Do not pretend the outputs are voice-coupled.

Then read the chosen voice profile so the rest of this skill can apply it.

After producing a draft and before returning it, run the anti-examples filter:

Read the anti_examples.pairs block in core/voice-profile.yml.
For each line in your draft, scan for matches against any bad: pattern (literal substrings, structural markers like negation-contrast, or rule-of-three lists).
If a line matches, rewrite it using the good: pattern as the model and the rule: line as the constraint.
Also reject any line that uses an aesthetic_crimes phrase or a red_flags pattern.
Return the cleaned draft.

Do not surface this filter to the user as a separate step. The user sees only the cleaned draft.

Runtime context

Before drafting, read brain/.snapshot.md. If it is missing, or its date: line is more than 3 days old, run python scripts/brain-snapshot.py --write first and read the fresh one - a stale snapshot read as current presents last week's flags and must-dos as today's, which is worse than no memory at all. If Python is unavailable, proceed without it and say so. Use the open-flags block to avoid topics that contradict current operator stance. Use the must-do block to lean the draft toward what the operator is actively working on. Use the voice and brand blocks (if present) to set tone. The freshness check above is not optional: skipping the regeneration and reading a week-old snapshot is the one way this block makes output worse.

Find the ONE core insight before adapting. A repurpose has one argument across every channel, not a different argument per platform.

Channel selection (brand-aware)

If brand voice is loaded, read brands/<slug>/positioning.yml. Filter the channel list:

Include channels in positioning.channels.primary and positioning.channels.secondary.
Exclude channels in positioning.channels.off_limits - never suggest these.
If the user explicitly asks for a channel that is off-limits, surface the conflict: "Positioning says <channel> is off-limits for <brand>. Want me to override for this piece, or skip that channel?"

If operator voice is loaded (no brand), include all channels by default but lean toward channels the operator has used recently per brain/log.md if that signal is available.

Channel Specifications

LinkedIn Post

100-300 words, line breaks between thoughts, hook first, no hashtags, arrows for lists

YouTube Script

3-5 minutes, conversational, Hook/Story/Framework/Takeaway, [B-ROLL] markers

Instagram Caption

50-150 words, scroll-stopper first line, short lines, no hashtags

Email Newsletter

200-500 words, lead with the point, one insight, casual direct tone

Twitter/X Thread

3-7 tweets, first tweet standalone value, one idea per tweet

Website Copy

Clear hierarchy, scannable, SEO-aware not SEO-driven

Internal Doc / SOP

Clear, direct, industry terms when they serve clarity, anti-AI check relaxed

Repurposing Rules

Don't just shorten. Each platform has a different angle.
Preserve the core insight. It should survive every adaptation.
Match the energy. LinkedIn = thought leadership. Instagram = personal. YouTube = teaching. Email = intimate.
Don't repeat yourself across channels. Find a different angle for each.
Apply the founder's voice to every output. Run anti-AI self-check on public content.

Output Format

SOURCE: [Brief description of original content]
CORE INSIGHT: [One sentence]
---
LINKEDIN POST
[content]
---
YOUTUBE SCRIPT
[content]
---
INSTAGRAM CAPTION
[content]