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 ur-grue/autopunk-media-skills --skill platform-distribution-advisorgit clone --depth 1 https://github.com/ur-grue/autopunk-media-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/ur-grue/autopunk-media-skills/platform-distribution-advisor)<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.
<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>- NVIDIA SkillSpector pass
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 | $0.00045 | $0.01320 |
| Opus 5 | $0.00023 | $0.00660 |
| Sonnet 5 | $0.00009 | $0.00264 |
| Haiku 4.5 | $0.00005 | $0.00132 |
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.
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
- 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)
- Matches the topic and intended audience to the likely user base of each candidate platform, noting where the audience overlap is strongest
- 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
- 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)
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.
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.
- 12d ago First seen · 95 lines · 45 tokens per session scan A 46f8e6ba4a54
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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