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 skills add iker-gonzalez/antwork-skills --skill antwork-repurposegit clone --depth 1 https://github.com/iker-gonzalez/antwork-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/iker-gonzalez/antwork-skills/antwork-repurpose)<a href="https://agentmods.dev/skills/iker-gonzalez/antwork-skills/antwork-repurpose"><img src="https://agentmods.dev/badge/skills/iker-gonzalez/antwork-skills/antwork-repurpose/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/iker-gonzalez/antwork-skills/antwork-repurpose"><img src="https://agentmods.dev/badge/skills/iker-gonzalez/antwork-skills/antwork-repurpose.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What 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 5.1 | $0.00103 | $0.00993 |
| Opus 5 | $0.00051 | $0.00496 |
| Sonnet 5 | $0.00021 | $0.00199 |
| Haiku 4.5 | $0.00010 | $0.00099 |
Grade A, and why
antwork-repurpose 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 10d ago.
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 — 60 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Repurposing one piece into platform-native posts
Antwork binds each post to a single account, and platform is derived from that account. Repurposing means writing a distinct, native version per platform — never one body copy-pasted everywhere — and grouping them under a shared campaign_id. This workflow codifies the mistakes assistants make when atomizing content.
1. Anchor the source
Identify the one source piece and its core idea. If the user hasn't pasted it, ask for the text, URL, or transcript. Extract the spine before reshaping:
- The single biggest claim or takeaway.
- 3–5 supporting points or moments that can each stand alone.
- Any quotable line, stat, or hook.
This spine is what gets reshaped per platform — not the prose itself.
2. Pick targets and pull each voice
Confirm which accounts to publish to (list_social_accounts if unsure — note account_id, platform, token health). For each target platform, before writing:
get_post_context(platform, account_id)— brand, that account's voice profile, recent posts,voiceStaleflag. Each account has its own voice; LinkedIn-you and X-you are not the same writer. IfvoiceStale, say so and offer theantwork-voicerefresh first.
3. Reshape — do not reuse
Write a native variant per platform. Reusing one body across platforms is the core failure: X's 280-char cap mangles LinkedIn prose, and LinkedIn-length paragraphs look broken on Threads. Reshape for each:
- X (280) — the sharpest single claim, or a thread broken into beats. No fluff.
- Threads (500) — conversational, one idea, lighter than LinkedIn.
- LinkedIn (3000) — room to tell the story; hook line, whitespace, a takeaway. Longer (300–600 words) is fine only here.
- Instagram (2200) — caption that works under a visual; front-load the hook.
- Facebook / YouTube / Pinterest / TikTok — match the platform's norm and limit.
Honor every hard limit (X 280, Threads 500, Pinterest 800, IG 2200, LinkedIn 3000, TikTok 4000, YouTube 5000, FB 63206) — schedule_post/publish_post reject anything over. Match the voice profile's tone, emoji and hashtag policy, and CTA style per account. Avoid AI tells ("Here's the thing:", "Let me break it down", emoji-heavy openers).
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.
- 10d ago First seen · 60 lines · 103 tokens per session scan A 7697bfb666c9
antwork-repurpose is a skill published in the GitHub repository iker-gonzalez/antwork-skills (0 stars, last pushed 2mo ago), licensed MIT. It adds 103 tokens to every session and 993 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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