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 agentmods add skills/moses607/socialforge/repurpose-masternpx skills add moses607/socialforge --skill repurpose-mastergit clone --depth 1 https://github.com/moses607/socialforgeWhat 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 | $0.00107 | $0.01200 |
| Opus 5 | $0.00053 | $0.00600 |
| Sonnet 5 | $0.00021 | $0.00240 |
| Haiku 4.5 | $0.00011 | $0.00120 |
Grade A, and why
repurpose-master 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 yesterday.
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 — 65 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Repurpose Master
One deliberate long asset contains 30-50 pieces of short-form content — most creators publish it once and waste 95% of the value. The unlock is atomization: every quotable line, mini-lesson, hot take, story, and Q&A is a standalone clip with its own hook. You are not slicing the video into equal chunks; you are hunting the moments that already spike, then rebuilding each as a self-contained piece with a hook that assumes zero context. One idea per clip is non-negotiable — a clip that tries to say two things gets swiped on both.
1. Mine the asset for atomic moments
- Pass through the full asset and timestamp every candidate: a quotable line, a counterintuitive claim, a mini-framework, a personal story, a sharp Q&A exchange, a strong reaction or laugh.
- Tag each by type — QUOTE, LESSON, HOT-TAKE, STORY, Q&A, DEMO — because type dictates format and platform.
- Score for standalone strength: does it make sense with no setup? Does it provoke, teach, or surprise in under 3s? Kill anything that needs the surrounding 5 minutes.
- Target 30+ from a 45-60 min asset. Dense assets yield more; don't force weak cuts to hit a number.
2. Spec each cut
- Assign platform by fit: hot takes and quotes → TikTok/Reels/Shorts; frameworks and lessons → carousel + LinkedIn text; stories → Reels + Shorts; Q&A → Shorts + tweet.
- Write a fresh hook per clip — the source's opening line is almost never the hook. The strongest sentence usually sits 10-20s into the moment; open there.
- Set length, aspect ratio (9:16 vertical, 1:1 square, 16:9 native), and on-screen text keyword.
- One asset feeds many formats: the same 40s moment becomes a vertical clip, a quote-card image, a carousel slide, and a text post — four pieces, one source.
3. Batch workflow
- Mine once, spec all 30+ before editing anything — context-switching between watching and editing is the time sink.
- Group by format and cut in batches (all vertical clips, then all quote cards, then all carousels).
- Stagger the calendar: never publish two derivatives of the same moment on the same platform same day.
- Track which derivatives outperform, then commission more long assets around those angles.
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.
- yesterday First seen · 65 lines · 107 tokens per session scan A 49e659a961b7
repurpose-master is a skill published in the GitHub repository moses607/socialforge (2 stars, last pushed 1mo ago), licensed MIT. It adds 107 tokens to every session and 1,200 once invoked, about $0.0005 per session on Opus 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 2026-08-31.
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