platform-distribution-advisor

platform-distribution-advisor is a skill for Claude Code from ur-grue/autopunk-media-skills. It costs 45 tokens per session (1,320 once invoked), scanned A, original, MIT.

A tool that ranks suitable platforms for publishing or redistributing finished content and briefly explains each recommendation.

In plain words
What is it for?
Creating distribution plans based on content type, topic, audience, length, existing platforms, payment preference, and geographic focus.
Why use it?
It reduces guesswork when deciding where an article, video, audio piece, photo essay, or data visualization is most likely to fit its audience.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the autopunk-media-skills plugin — 187 skills shipped together

Good fit Creating distribution plans based on content type, topic, audience, length, existing platforms, payment preference, and geographic focus.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/ur-grue/autopunk-media-skills/platform-distribution-advisor
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 ur-grue/autopunk-media-skills --skill platform-distribution-advisor
Clone the repo
git clone --depth 1 https://github.com/ur-grue/autopunk-media-skills

Made for: Claude Code.

Or install autopunk-media-skills, the plugin that ships this one along with the rest of its 187 skills.

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 platform-distribution-advisor

README.md
[![agentmods](https://agentmods.dev/badge/skills/ur-grue/autopunk-media-skills/platform-distribution-advisor/github.svg)](https://agentmods.dev/skills/ur-grue/autopunk-media-skills/platform-distribution-advisor)
Your own site
<a href="https://agentmods.dev/skills/ur-grue/autopunk-media-skills/platform-distribution-advisor"><img src="https://agentmods.dev/badge/skills/ur-grue/autopunk-media-skills/platform-distribution-advisor/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 platform-distribution-advisor

Your own site · 80×15
<a href="https://agentmods.dev/skills/ur-grue/autopunk-media-skills/platform-distribution-advisor"><img src="https://agentmods.dev/badge/skills/ur-grue/autopunk-media-skills/platform-distribution-advisor.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 45 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,320 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 $0.00045 $0.01320
Opus 5 $0.00023 $0.00660
Sonnet 5 $0.00009 $0.00264
Haiku 4.5 $0.00005 $0.00132

Measured 12d ago against content hash 46f8e6ba4a54, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

platform-distribution-advisor 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 12d 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/audience-distribution/platform-distribution-advisor/SKILL.md · 95 lines

How it starts

The opening of the file, as written. The whole thing — 95 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Platform Distribution Advisor

What This Skill Does

Recommends the best platforms for distributing a finished piece of content, with a ranked list and a brief rationale for each recommendation based on the content type, format, length, and intended audience.

When To Use This Skill

  • You have finished content and are deciding where to publish or syndicate it
  • You are building a multi-platform distribution plan for a story, episode, or video
  • You want to reach a new audience segment beyond your primary publication
  • You are adapting existing content for redistribution and need to know which platforms suit it best

What You Need To Provide

Required:

  • Content type (article, video, audio, photo essay, data visualization, etc.)
  • Topic or subject area (a brief description is enough — one or two sentences)
  • Intended audience (professionals, general public, younger readers, regional audience, etc.)
  • Content length or duration

Optional:

  • Your primary publication or home platform (to help identify gaps)
  • Any platforms you are already using, so recommendations stay non-redundant
  • Paid vs. organic distribution preference
  • Geographic focus (local, national, international)

How the Assistant Approaches This

  1. Identifies the content category — text, audio, video, visual — and cross-references it with which platforms are structurally suited to that format (e.g., long-form text does not perform on short-video platforms)
  2. Matches the topic and intended audience to the likely user base of each candidate platform, noting where the audience overlap is strongest
  3. Produces a ranked list of three to five platforms with a short rationale for each, including one note on what adaptation (if any) the content would need for that platform
  4. Flags any mismatch risks — for example, platforms where the content's length or tone is likely to underperform

Output Format

A ranked list of three to five platforms. Each entry includes:

  • Platform name
  • One-sentence rationale (why this content fits this platform and this audience)
  • One-line adaptation note (what, if anything, needs adjusting before publishing there)

Read the full file on GitHub · 95 lines

Files

What ships with it

1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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. 12d ago First seen · 95 lines · 45 tokens per session scan A 46f8e6ba4a54

Subscribe to this mod's changes

platform-distribution-advisor is a skill published in the GitHub repository ur-grue/autopunk-media-skills (30 stars, last pushed 11d ago), licensed MIT. It adds 45 tokens to every session and 1,320 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 2026-08-30.

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