Borrowing it
Nothing to install: this file belongs to briancl2/CustomerNewsletter. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/briancl2/CustomerNewsletter/main/.github/skills/video-matching/SKILL.mdgit clone --depth 1 https://github.com/briancl2/CustomerNewsletterWrote 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/briancl2/customernewsletter/video-matching)<a href="https://agentmods.dev/skills/briancl2/customernewsletter/video-matching"><img src="https://agentmods.dev/badge/skills/briancl2/customernewsletter/video-matching/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/briancl2/customernewsletter/video-matching"><img src="https://agentmods.dev/badge/skills/briancl2/customernewsletter/video-matching.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 | $0.00077 | $0.01297 |
| Opus 5 | $0.00039 | $0.00648 |
| Sonnet 5 | $0.00015 | $0.00259 |
| Haiku 4.5 | $0.00008 | $0.00130 |
Grade A, and why
video-matching 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.
How it starts
The opening of the file, as written. The whole thing — 118 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Video Matching
Enrich newsletter entries with links to matching official YouTube videos from the VS Code and GitHub channels.
Quick Start
- Read the assembled newsletter from
output/YYYY-MM_month_newsletter.md - Fetch RSS feeds from VS Code and GitHub YouTube channels
- Match videos to newsletter entries by topic
- Add
[Video (Xm)](URL)links to matched entries - Write enriched newsletter back to
output/YYYY-MM_month_newsletter.md
Inputs
- Newsletter:
output/YYYY-MM_month_newsletter.md(required) - YouTube RSS feeds (fetch these):
- VS Code channel:
https://www.youtube.com/feeds/videos.xml?channel_id=UCs5Y5_7XK8HLDX0SLNwkd3w - GitHub channel:
https://www.youtube.com/feeds/videos.xml?channel_id=UC7c3Kb6jYCRj4JOHHZTxKsQ
- VS Code channel:
Output
- Enriched Newsletter:
output/YYYY-MM_month_newsletter.md(overwrite in place) - Video Matching Report:
workspace/newsletter_phase4_6_video_matches_YYYY-MM-DD.md - Record receipt with phase id
phase4_6_video
Core Workflow
Step 1: Fetch Video Feeds
Fetch both YouTube RSS feeds. Each returns the 15 most recent videos with:
<title>— Video title<link>— YouTube URL (format:https://www.youtube.com/watch?v=VIDEO_IDor/shorts/VIDEO_ID)<published>— Publication date<media:description>— Full description with chapters, links, and speaker info
Parse both feeds and build a combined video inventory.
Step 2: Filter Videos
INCLUDE videos that are:
- Published within the newsletter's DATE_RANGE (or up to 2 weeks before/after)
- About GitHub Copilot, VS Code, agents, MCP, security, or enterprise features
- Full-length videos (>2 minutes) or Shorts that directly demonstrate a named feature
EXCLUDE:
- Shorts that are generic teasers without specific feature content
- Open Source Friday episodes about non-GitHub projects
- Non-English content
- General tutorials not tied to a specific feature in the newsletter
Step 3: Match Videos to Newsletter Entries
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.
- 10d ago First seen · 118 lines · 77 tokens per session scan A f99053203699
video-matching is a skill published in the GitHub repository briancl2/CustomerNewsletter (11 stars, last pushed 3mo ago), licensed MIT. It adds 77 tokens to every session and 1,297 once invoked, about $0.0004 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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