content-pillar-atomizer

content-pillar-atomizer is a skill for Claude Code, Codex from Gingg7260/affiliate-skills. It costs 136 tokens per session (2,618 once invoked), scanned A, original, MIT.

A content-repurposing skill that turns one blog post or article into 15–30 smaller pieces for platforms such as X, LinkedIn, Reddit, TikTok, email, and Threads. It adapts each piece to the platform instead of simply copying the original text.

In plain words
What is it for?
Use it to turn a full article or a supplied URL into platform-specific posts, comments, short-video ideas, emails, or other smaller pieces.
Why use it?
It saves you from creating every social post from scratch while avoiding identical wording everywhere. Each version can fit the platform's usual format and audience.

Skill for Claude CodeCodex

Which agent this was written for is unclear — built for openclaw. Also seen: mentions Claude Code; built for openclaw; mentions Gemini CLI.

Good fit Use it to turn a full article or a supplied URL into platform-specific posts, comments, short-video ideas, emails, or other smaller pieces.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/gingg7260/affiliate-skills/content-pillar-atomizer
Install

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.

Any agent
npx skills add Gingg7260/affiliate-skills --skill content-pillar-atomizer
Clone the repo
git clone --depth 1 https://github.com/Gingg7260/affiliate-skills

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for content-pillar-atomizer

README.md
[![agentmods](https://agentmods.dev/badge/skills/gingg7260/affiliate-skills/content-pillar-atomizer/github.svg)](https://agentmods.dev/skills/gingg7260/affiliate-skills/content-pillar-atomizer)
Your own site
<a href="https://agentmods.dev/skills/gingg7260/affiliate-skills/content-pillar-atomizer"><img src="https://agentmods.dev/badge/skills/gingg7260/affiliate-skills/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.

agentmods 80×15 button for content-pillar-atomizer

Your own site · 80×15
<a href="https://agentmods.dev/skills/gingg7260/affiliate-skills/content-pillar-atomizer"><img src="https://agentmods.dev/badge/skills/gingg7260/affiliate-skills/content-pillar-atomizer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 136 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,618 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00136 $0.02618
Opus 5 $0.00068 $0.01309
Sonnet 5 $0.00027 $0.00524
Haiku 4.5 $0.00014 $0.00262

Measured 10d ago against content hash a0e7d0d33a27, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

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 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.

skills/content/content-pillar-atomizer/SKILL.md · 286 lines

How it starts

The opening of the file, as written. The whole thing — 286 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

  1. If URL provided, use web_fetch to retrieve content
  2. Extract: key insights (5-8), data points, quotes, frameworks, stories, opinions
  3. Identify the "atomic units" — self-contained ideas that work independently
  4. Note the product/affiliate angle (if present)

Read the full file on GitHub · 286 lines

Changes

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.

  1. 10d ago First seen · 286 lines · 136 tokens per session scan A a0e7d0d33a27

Subscribe to this mod's changes

content-pillar-atomizer is a skill published in the GitHub repository Gingg7260/affiliate-skills (5 stars, last pushed today), licensed MIT. It adds 136 tokens to every session and 2,618 once invoked, about $0.0007 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.

Related

Other skills, from other repositories

content-pillar-atomizer

Take 1 blog post or article and generate 15-30 platform-native micro-content pieces. Not reformatting — re-contextualizing for each platform's culture. Triggers on: "atomize this content", "repurpose my blog post", "turn this into social posts", "content atomizer", "pillar content", "one to many content", "repurpose…

Affitor/affiliate-skills · 136 tokens

content-pillar-atomizer

Take 1 blog post or article and generate 15-30 platform-native micro-content pieces. Not reformatting — re-contextualizing for each platform's culture. Triggers on: "atomize this content", "repurpose my blog post", "turn this into social posts", "content atomizer", "pillar content", "one to many content", "repurpose…

gabrielmoreira/agent-skills-mirror · 136 tokens

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