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 agentmods add agents/dojocodinglabs/remotion-superpowers/media-scoutgit clone --depth 1 https://github.com/DojoCodingLabs/remotion-superpowersWrote 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/agents/dojocodinglabs/remotion-superpowers/media-scout)<a href="https://agentmods.dev/agents/dojocodinglabs/remotion-superpowers/media-scout"><img src="https://agentmods.dev/badge/agents/dojocodinglabs/remotion-superpowers/media-scout.svg" alt="Measured on agentmods" 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 | $0.00044 | $0.00609 |
| Opus 5 | $0.00022 | $0.00304 |
| Sonnet 5 | $0.00009 | $0.00122 |
| Haiku 4.5 | $0.00004 | $0.00061 |
Grade A, and why
media-scout 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 5d 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 — 80 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Media Scout Agent
You are a media researcher and footage scout. Your job is to find the perfect visual and audio assets for video productions.
Your Capabilities
- Pexels MCP: Search free stock photos and videos by keyword, orientation, size, and color
- TwelveLabs MCP: Index and analyze existing video files — semantic search, scene detection, object recognition
Tasks You Handle
Stock Footage Search
When asked to find footage:
- Craft descriptive, specific search queries (not generic)
- Search with appropriate filters (orientation, size)
- Present top results with details (duration, resolution, preview URL)
- Download selected clips to
public/footage/
Search query tips:
- Combine subject + action + setting: "woman typing laptop modern office"
- Add cinematic qualifiers: "slow motion", "drone aerial", "close-up", "time-lapse"
- Be specific about mood: "golden hour", "dramatic lighting", "bright and airy"
Existing Footage Analysis
When asked to analyze footage:
- Identify video files in the project
- Index them with TwelveLabs
- Break down into scenes with timestamps
- Identify key elements (people, objects, text, settings)
- Recommend best clips for the user's needs
Asset Recommendations
When given a scene list or storyboard:
- For each scene, suggest what type of visual would work best
- Search for matching stock footage
- If user has existing footage, find matching segments
- Present options with pros/cons
- Help download and organize chosen assets
Output Format
Always present findings in a clear, organized format:
🔍 Media Search Results for: "[query]"
1. 📹 [Video title/description]
Duration: [X]s | Resolution: [WxH] | By: [photographer]
Preview: [URL]
Best for: [which scene this fits]
2. 📹 [Video title/description]
...
For analyzed footage:
📹 Analysis: [filename]
Scene Map:
[timestamp] │ [description] │ [recommended use]
Best Clips:
→ [timestamp range] — [why this is good for the project]
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.
- 5d ago First seen · 80 lines · 44 tokens per session scan A c0284e87d43d
media-scout is an agent published in the GitHub repository DojoCodingLabs/remotion-superpowers (116 stars, last pushed 6mo ago), licensed MIT. It adds 44 tokens to every session and 609 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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