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 BingHanOfUESTC/open_agent_team --skill media-asset-sourcinggit clone --depth 1 https://github.com/BingHanOfUESTC/open_agent_teamWrote 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/binghanofuestc/open_agent_team/media-asset-sourcing)<a href="https://agentmods.dev/skills/binghanofuestc/open_agent_team/media-asset-sourcing"><img src="https://agentmods.dev/badge/skills/binghanofuestc/open_agent_team/media-asset-sourcing/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/binghanofuestc/open_agent_team/media-asset-sourcing"><img src="https://agentmods.dev/badge/skills/binghanofuestc/open_agent_team/media-asset-sourcing.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 | $0.00046 | $0.00750 |
| Opus 5 | $0.00023 | $0.00375 |
| Sonnet 5 | $0.00009 | $0.00150 |
| Haiku 4.5 | $0.00005 | $0.00075 |
Grade A, and why
media-asset-sourcing 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 7d 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 — 148 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Media Asset Sourcing
This skill turns media needs into local PPT-ready assets and source-traced video links.
Search Plan
Create:
materials/media/media_search_plan.md
For each needed visual:
slide id
visual purpose
preferred media type: photo | screenshot | logo | chart | icon | video | thumbnail
query terms
preferred sources
rights requirement
fallback plan
Source Preference
Prefer:
Boss-provided media
official product/company/project pages
press kits and media kits
openly licensed repositories
Wikimedia Commons with license review
Unsplash/Pexels/Pixabay for generic photos when license permits
official YouTube/Vimeo/Bilibili pages for video links
dataset/benchmark/project pages for technical screenshots
Avoid:
random reposted images
watermarked stock previews
unknown-license social media uploads
unrelated decorative photos
AI-generated images unless Boss accepts them
video mirrors from unofficial accounts
Download and Prepare
Images:
download/copy to materials/images/raw/
crop/resize to materials/images/processed/
record source URL, license/risk, alt text, caption, slide use
reference processed_path in deck_spec
Videos:
download only when allowed and practical
otherwise use official video_url
prepare thumbnail_path when possible
record duration, source URL, title, rights risk, and recommended slide
reference video_path or video_url + thumbnail_path in deck_spec
Manifest
Create:
materials/media/media_manifest.json
Shape:
{
"images": [
{
"id": "hero_image",
"processed_path": "materials/images/processed/hero.jpg",
"source_url": "https://example.com/image",
"license": "unknown | public-domain | cc-by | owned | permitted",
"rights_risk": "low | medium | high",
"alt": "Short alt text",
"recommended_slide": "S03"
}
],
"videos": [
{
"id": "product_demo_video",
"title": "Product demo",
"video_url": "https://example.com/video",
"video_path": "",
"thumbnail_path": "materials/media/thumbnails/product_demo.jpg",
"source_url": "https://example.com/video",
"rights_risk": "low",
"recommended_slide": "S08",
"insert_mode": "link_card"
}
]
}
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.
- 7d ago First seen · 148 lines · 46 tokens per session scan A b5861b2b10db
media-asset-sourcing is a skill published in the GitHub repository BingHanOfUESTC/open_agent_team (106 stars, last pushed 2mo ago), licensed MIT. It adds 46 tokens to every session and 750 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.
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