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 floomhq/moto --skill review-videogit clone --depth 1 https://github.com/floomhq/motoWrote 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/floomhq/moto/review-video)<a href="https://agentmods.dev/skills/floomhq/moto/review-video"><img src="https://agentmods.dev/badge/skills/floomhq/moto/review-video/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/floomhq/moto/review-video"><img src="https://agentmods.dev/badge/skills/floomhq/moto/review-video.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 | $0.00108 | $0.00615 |
| Opus 5 | $0.00054 | $0.00308 |
| Sonnet 5 | $0.00022 | $0.00123 |
| Haiku 4.5 | $0.00011 | $0.00061 |
Grade A, and why
review-video 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.
What it actually says
Video Review
Review videos by extracting frames and analyzing them visually.
Workflow
Step 1: Extract frames
python3 ~/.claude/skills/review-video/scripts/extract_frames.py <video_path> --smart -n 10 --cleanup
Step 2: Read ALL frames in parallel
Read every frame path from output using Read tool. Parallel reads for speed.
Step 3: Cleanup temp files
Run the cleanup command printed at the end (if --cleanup was used).
Step 4: Provide structured review
## Video Review: [filename]
**Metadata**: [resolution] | [duration] | [fps] fps | [codec]
### Overall Assessment
[1-2 sentences]
### Frame-by-Frame Notes
- > [0:00] Opening: [observation]
- o [0:05] [observation]
- * [0:10] Scene change: [observation]
- = [0:15] Closing: [observation]
### Issues Found
- [ ] Issue at [timestamp]: [description]
### Verdict
[PASS / NEEDS FIXES / FAIL] - [reason]
Options
| Flag | Description |
|---|---|
-n NUM |
Number of frames (default: 10) |
--smart |
Use scene detection (recommended) |
--threshold FLOAT |
Scene sensitivity 0.0-1.0 (default: 0.1, lower=more sensitive) |
--cleanup |
Print cleanup command for temp files |
--json |
Output as JSON |
-o DIR |
Custom output directory |
-q NUM |
JPEG quality 1-31 (default: 2, lower=better) |
Frame Source Icons
| Icon | Meaning |
|---|---|
| > | Start of video |
| = | End of video |
| * | Scene change detected |
| o | Evenly-spaced filler |
Frame Count Guidelines
| Use Case | Command |
|---|---|
| Quick check | -n 5 |
| Standard | -n 10 --smart |
| Animation | -n 20 --smart --threshold 0.05 |
| Debug | -n 30 --smart |
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 · 84 lines · 108 tokens per session scan A b3d5b4382d7a
review-video is a skill published in the GitHub repository floomhq/moto (32 stars, last pushed 3mo ago), licensed MIT. It adds 108 tokens to every session and 615 once invoked, about $0.0005 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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