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 sanky369/vibe-building-skills --skill content-atomizergit clone --depth 1 https://github.com/sanky369/vibe-building-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/sanky369/vibe-building-skills/content-atomizer)<a href="https://agentmods.dev/skills/sanky369/vibe-building-skills/content-atomizer"><img src="https://agentmods.dev/badge/skills/sanky369/vibe-building-skills/content-atomizer/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/sanky369/vibe-building-skills/content-atomizer"><img src="https://agentmods.dev/badge/skills/sanky369/vibe-building-skills/content-atomizer.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 | $0.00137 | $0.02010 |
| Opus 5.5 | $0.00055 | $0.00804 |
| Sonnet 5.5 | $0.00027 | $0.00402 |
| Haiku 4.5 | $0.00014 | $0.00201 |
Grade A, and why
content-atomizer 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 2mo 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 — 137 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Content Atomizer
Break one substantial piece of content into many platform-native pieces. Prime directive: adapt, never excerpt — each atomic piece must stand alone as if written for that platform on purpose, carrying the user's voice, while format and length obey the platform. The second rule: atomize ideas, not paragraphs — you extract the content's core ideas first, then re-express each idea per platform.
When to use / when not to
- Use when there is existing long-form source content and the goal is distribution across channels.
- If the user needs the long-form piece written first, use
skills/marketing/seo-content— then come back. - If the user wants one great tweet/thread crafted and researched from scratch (not derived from source content), use
skills/marketing/tweet-writer— it does niche research this skill skips. - If the user wants a full newsletter issue (not just an item), hand the source to
skills/marketing/newsletter.
Intake
Ask in one batch, only what's missing:
- The seed content — the actual text/transcript (or link). Verify it's substantial enough: multiple distinct ideas and a point of view. If it's thin (one idea, <~500 words), say so and offer a single-platform adaptation instead of a pack.
- Active platforms — where does the user actually publish, and which 1–2 matter most?
- Goal — reach/followers, traffic back to the source, or list growth? (This sets the CTAs.)
- Voice — brand-voice guide or sample posts (use
skills/marketing/brand-voiceoutput if it exists).
Don't ask which formats they want — that's your job to propose in Step 3. If platforms are unknown, default to LinkedIn + X + newsletter item and say so. State assumptions and proceed — don't stall.
Workflow
1. Extract the idea inventory
Read the seed content and pull 5–10 discrete ideas, each tagged by type — the type determines which formats it can power:
- Core concept — the piece's main argument
- Framework/process — anything with steps or named parts (best carousel/thread material)
- Story/example — narratives and cases (best LinkedIn/newsletter material)
- Surprising insight or contrarian take — the counterintuitive bits (best hook material)
- Actionable tip — standalone do-this-today advice (best short-video/single-post material)
- Quotable line — sentences that sting (quote graphics, thread closers)
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.
- 2mo ago First seen · 137 lines · 137 tokens per session scan A b79184bd989d
content-atomizer is a skill published in the GitHub repository sanky369/vibe-building-skills (31 stars, last pushed 3mo ago), licensed MIT. It adds 137 tokens to every session and 2,010 once invoked, about $0.0005 per session on Opus 5.5. 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 2026-08-30.
content-atomizer compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| content-atomizersanky369/vibe-building-skills | Skill | 31 | 3mo ago | MIT | A | 137 | Claude Code, Codex |
| ads-youtubeAgriciDaniel/claude-ads | Skill | 11k | 5d ago | MIT | A | 84 | Claude Code |
| ads-launchAgriciDaniel/claude-ads | Skill | 11k | 5d ago | MIT | A | 45 | Claude Code |
| happiness-skillkangarooking/cangjie-skill | Skill | 12k | 1mo ago | MIT | A | 136 | Claude Code, Codex |
| setup-matt-pocock-skillsdevcxl/mattpocock-skills-zh | Skill | 530 | 3d ago | MIT | A | 43 | Claude Code, Codex |
| aiwg-regenerate-copilotjmagly/aiwg | Skill | 229 | yesterday | MIT | A | 25 | Claude Code, Codex |
| steward-prep-deliveryjmagly/aiwg | Skill | 229 | yesterday | MIT | A | 32 | Claude Code, Codex |