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 gabrielmoreira/agent-skills-mirror --skill content-pillar-atomizergit clone --depth 1 https://github.com/gabrielmoreira/agent-skills-mirrorWrote 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/gabrielmoreira/agent-skills-mirror/content-pillar-atomizer)<a href="https://agentmods.dev/skills/gabrielmoreira/agent-skills-mirror/content-pillar-atomizer"><img src="https://agentmods.dev/badge/skills/gabrielmoreira/agent-skills-mirror/content-pillar-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/gabrielmoreira/agent-skills-mirror/content-pillar-atomizer"><img src="https://agentmods.dev/badge/skills/gabrielmoreira/agent-skills-mirror/content-pillar-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 | $0.00136 | $0.03030 |
| Opus 5.5 | $0.00054 | $0.01212 |
| Sonnet 5.5 | $0.00027 | $0.00606 |
| Haiku 4.5 | $0.00014 | $0.00303 |
Grade A, and why
content-pillar-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.
This is a copy
100% identical to content-pillar-atomizer — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 317 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Content Pillar Atomizer
Take 1 blog post or article and generate 15-30 platform-native micro-content pieces. This is NOT reformatting — it's re-contextualizing each piece for the platform's culture, format, and audience expectations. A LinkedIn post reads nothing like a Reddit comment, even if they carry the same insight.
Stage
S2: Content Creation — This IS content creation, just at 10x scale. One piece of deep work becomes a month of social content.
When to Use
- User has a blog post, article, or long-form content and wants to maximize its reach
- User asks to "repurpose" or "atomize" content
- User says "turn this into social posts", "content multiplication", "pillar content"
- After
affiliate-blog-builder(S3) produces an article — atomize it into social - User wants to maintain consistent content output without creating from scratch daily
Input Schema
pillar_content: string # REQUIRED — the full blog post/article text, or URL to fetch
platforms: string[] # OPTIONAL — target platforms
# Options: "twitter", "linkedin", "reddit", "tiktok", "email", "threads"
# Default: ["twitter", "linkedin", "reddit"]
product: object # OPTIONAL — affiliate product being promoted
name: string
url: string
reward_value: string
mode: string # OPTIONAL — "quality" | "volume"
# Default: "quality"
tone: string # OPTIONAL — "professional" | "casual" | "edgy" | "educational"
# Default: inferred from pillar content
Chaining from S3: If affiliate-blog-builder was run, use its output article as pillar_content.
Chaining from S1 monopoly-niche-finder: Use monopoly_niche positioning to angle all micro-content.
Workflow
Step 1: Analyze Pillar Content
- If URL provided, use
web_fetchto retrieve content - Extract: key insights (5-8), data points, quotes, frameworks, stories, opinions
- Identify the "atomic units" — self-contained ideas that work independently
- Note the product/affiliate angle (if present)
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 · 317 lines · 136 tokens per session scan A 0ca41c3c85bc
content-pillar-atomizer is a skill published in the GitHub repository gabrielmoreira/agent-skills-mirror (20 stars, last pushed yesterday), licensed MIT. It adds 136 tokens to every session and 3,030 once invoked, about $0.0005 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to content-pillar-atomizer, differing in 0 lines, and is treated as a copy.
content-pillar-atomizer compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| content-pillar-atomizergabrielmoreira/agent-skills-mirror | Skill | 20 | yesterday | MIT | A | 136 | Claude Code, Codex |
| content-pillar-atomizerAffitor/affiliate-skills | Skill | 771 | 19d ago | MIT | A | 136 | Claude Code, Codex |
| content-pillar-atomizerGingg7260/affiliate-skills | Skill | 5 | 26d ago | MIT | A | 136 | Claude Code, Codex |
| reddit-post-writerAffitor/affiliate-skills | Skill | 771 | 19d ago | MIT | A | 133 | Claude Code |
| tiktok-script-writerAffitor/affiliate-skills | Skill | 771 | 19d ago | MIT | A | 138 | Claude Code |
| twitter-thread-writerAffitor/affiliate-skills | Skill | 771 | 19d ago | MIT | A | 116 | Claude Code |
| viral-post-writerAffitor/affiliate-skills | Skill | 771 | 19d ago | MIT | A | 160 | Claude Code, Codex |