multi-platform-distribution

multi-platform-distribution is a skill for Claude Code, Codex from oyi77/1ai-skills. It costs 48 tokens per session (3,361 once invoked), scanned A, original, MIT.

A content repurposing workflow that turns one source piece into formats for platforms such as X, LinkedIn, YouTube, newsletters, TikTok, podcasts, Reddit, and Hacker News.

In plain words
What is it for?
It helps create platform-specific posts, scripts, articles, newsletters, outlines, and submissions, then schedule distribution and track results.
Why use it?
It removes the need to rewrite the same ideas manually for every platform and helps keep each version suited to that platform’s format.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Part of the 1ai-skills plugin — 209 skills, 4 commands shipped together

Good fit It helps create platform-specific posts, scripts, articles, newsletters, outlines, and submissions, then schedule distribution and track results.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/oyi77/1ai-skills/multi-platform-distribution
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 oyi77/1ai-skills --skill multi-platform-distribution
Clone the repo
git clone --depth 1 https://github.com/oyi77/1ai-skills

Made for: Claude Code, Codex.

Or install 1ai-skills, the plugin that ships this one along with the rest of its 209 skills, 4 commands.

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 multi-platform-distribution

README.md
[![agentmods](https://agentmods.dev/badge/skills/oyi77/1ai-skills/multi-platform-distribution/github.svg)](https://agentmods.dev/skills/oyi77/1ai-skills/multi-platform-distribution)
Your own site
<a href="https://agentmods.dev/skills/oyi77/1ai-skills/multi-platform-distribution"><img src="https://agentmods.dev/badge/skills/oyi77/1ai-skills/multi-platform-distribution/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 multi-platform-distribution

Your own site · 80×15
<a href="https://agentmods.dev/skills/oyi77/1ai-skills/multi-platform-distribution"><img src="https://agentmods.dev/badge/skills/oyi77/1ai-skills/multi-platform-distribution.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 48 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,361 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. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
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 $0.00048 $0.03361
Opus 5 $0.00024 $0.01681
Sonnet 5 $0.00010 $0.00672
Haiku 4.5 $0.00005 $0.00336

Measured 8d ago against content hash 6a2def509ec8, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

multi-platform-distribution 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 8d 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.

content/multi-platform-distribution/SKILL.md · 449 lines

How it starts

The opening of the file, as written. The whole thing — 449 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Overview

Transform a single piece of content into platform-specific formats, schedule distribution across channels, and track performance. Saves 80% of content marketing time by automating the repurposing pipeline. One blog post becomes a Twitter thread, LinkedIn article, YouTube script, newsletter edition, TikTok script, podcast outline, Reddit post, and Hacker News submission — each optimized for its platform's audience and format.

Required Tools

  • pandoc for format conversion
  • Python with markdown / jinja2 for templating
  • Twitter API v2 (now X API) for thread posting
  • LinkedIn API for article publishing
  • YouTube Data API for video metadata
  • Substack/Beehiiv API for newsletter
  • TikTok Content Posting API
  • Reddit API for post submission
  • Buffer/Hootsuite API for scheduling
  • Google Analytics / Plausible for tracking

Capabilities

  • Parse source content into semantic blocks (intro, key points, examples, conclusion)
  • Generate platform-specific versions respecting character limits, tone, and format
  • Auto-generate Twitter threads with proper numbering and hooks
  • Create LinkedIn posts with engagement-optimized structure
  • Generate YouTube scripts with timestamps and B-roll suggestions
  • Produce TikTok scripts with hook, value, CTA structure
  • Schedule posts at optimal times per platform
  • Track cross-platform performance in unified dashboard

When to Use

Trigger phrases:

  • "multi platform distribution"

  • "One piece of content becomes 10 — blog to Twitter thread, LinkedIn article, YouT"

  • "I wrote a blog post, distribute it everywhere"

  • "Turn this article into a Twitter thread and LinkedIn post"

  • "Repurpose our latest podcast episode into 10 pieces of content"

  • "Create a content calendar from our existing content library"

  • "This newsletter issue should also go on LinkedIn and as a blog"

When NOT to Use

  • Task is about content strategy, not creation (use strategy skills)
  • Task is about content distribution (use distribution skills)
  • You need to analyze content performance (use analytics skills)
  • Task is about content moderation (use moderation tools)
  • You don't have content guidelines
  • Task requires domain expertise (consult experts)

Read the full file on GitHub · 449 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. 8d ago First seen · 449 lines · 48 tokens per session scan A 6a2def509ec8

Subscribe to this mod's changes

multi-platform-distribution is a skill published in the GitHub repository oyi77/1ai-skills (12 stars, last pushed today), licensed MIT. It adds 48 tokens to every session and 3,361 once invoked, about $0.0002 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 2026-09-03.