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 naveedharri/benai-skills --skill yt-to-communitygit clone --depth 1 https://github.com/naveedharri/benai-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/naveedharri/benai-skills/yt-to-community)<a href="https://agentmods.dev/skills/naveedharri/benai-skills/yt-to-community"><img src="https://agentmods.dev/badge/skills/naveedharri/benai-skills/yt-to-community/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/naveedharri/benai-skills/yt-to-community"><img src="https://agentmods.dev/badge/skills/naveedharri/benai-skills/yt-to-community.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 | $0.00226 | $0.02289 |
| Opus 5.5 | $0.00090 | $0.00916 |
| Sonnet 5.5 | $0.00045 | $0.00458 |
| Haiku 4.5 | $0.00023 | $0.00229 |
Grade A, and why
yt-to-community 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 1mo 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 — 182 lines — stays where its author put it; the contents beside it link to each section on GitHub.
YouTube to Community Announcement Post
Convert a YouTube video into a ready-to-publish announcement post for the Accelerator's community on Circle. Output is a draft, in Ben's voice, with thumbnail attached and any resources/lead magnets surfaced.
Pipeline Position
This skill is step 1 of 2 in the YouTube repurposing pipeline.
yt-to-community(this skill): community post + thumbnail. Runs automatically on any YouTube URL.yt-to-course: course material. Runs only after the post is done and the user confirms.
When a YouTube URL lands in chat, do NOT ask "do you want a post or a course first?". The order is fixed: post first, then offer the course. The final step of this skill prompts the user about the course.
Why This Exists
Every Ben AI YouTube video needs a paired announcement post in the community. The post follows a specific format and voice. Doing this manually means watching the video, noting resources, drafting copy, and posting. This skill produces the draft from just a URL.
Profile boundary
All output writes to Profiles/Milan/Community/community-posts/. The thumbnail saves alongside as {date}-{slug}-thumbnail.jpg. Milan reviews the draft and publishes from Ben's Circle account manually. See [[yt-pipeline SPEC|SPEC.md]] for the full invariant.
The Flow
Step 1: Ingestion
Invoke the yt-ingestion-agent sub-agent with:
- youtube_url: the URL from the user's message
- output_dir: a working directory (default:
Profiles/Milan/Daily/{today}/yt-community-{video-id}/)
For community posts we don't need the video file itself, just transcript + metadata + thumbnail. The agent fetches all three.
If transcript fetching fails (rare but possible), ask the user to paste the transcript or provide the video description.
Step 2: Detect Resources and Lead Magnets
Scan the transcript for resource mentions:
- Tools named in the video (named software, websites, Chrome extensions)
- Lead magnets (free downloads, free templates, free skills, "link in description")
- Course references (existing accelerator courses)
- External URLs explicitly mentioned
What ships with it
2 files 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.
- 1mo ago Changed · +1 lines 80a947a94591
- 1mo ago First seen · 181 lines · 226 tokens per session scan A 94e637ef31d6
yt-to-community is a skill published in the GitHub repository naveedharri/benai-skills (74 stars, last pushed 16d ago), licensed MIT. It adds 226 tokens to every session and 2,289 once invoked, about $0.0009 per session on Opus 5.5. 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 2026-09-12.
Other skills, from other repositories
project
A single starting point for setting up an AI-assisted project in Claude Cowork. It asks questions about the work, reviews available add-ons, and creates project instructions, custom agents, and connected workflows.
doc-html-slide
A renderer that turns presentation content into a single HTML slide deck that opens directly in a browser. It creates a 16:9 slide sequence with navigation, fullscreen viewing, printing to PDF, and speaker-note controls.
cs-channel-message
A channel-message writing tool for search ads, advertising, customer relationship messages, and app notifications. It uses the NCM sequence—Need, Channel, Moment, Message, and CTA—to adapt wording to where and when customers see it.
media-higgsfield-explainer
A Higgsfield workflow for making non-photorealistic narrated explainer videos. It pairs each narration line with a 10-second animated clip and joins the clips into one finished video.
setup-mcp-connector
A step-by-step setup guide for connecting Cowork to services such as Google Drive, Notion, and Higgsfield, plus Korean public-data, document, statistics, architecture, and law services. It explains authentication, API keys, test calls, and troubleshooting.
media-gpt-image-prompt
An image-prompt writing tool that turns a natural-language idea into detailed prompts for GPT Image 2.5. It can also adapt the same idea for Gemini 3 Pro Image and Midjourney.