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 oaustegard/claude-skills --skill parsing-videogit clone --depth 1 https://github.com/oaustegard/claude-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/oaustegard/claude-skills/parsing-video)<a href="https://agentmods.dev/skills/oaustegard/claude-skills/parsing-video"><img src="https://agentmods.dev/badge/skills/oaustegard/claude-skills/parsing-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/oaustegard/claude-skills/parsing-video"><img src="https://agentmods.dev/badge/skills/oaustegard/claude-skills/parsing-video.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 | $0.00160 | $0.02247 |
| Opus 5 | $0.00080 | $0.01123 |
| Sonnet 5 | $0.00032 | $0.00449 |
| Haiku 4.5 | $0.00016 | $0.00225 |
Grade A, and why
parsing-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 8d 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 — 144 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Parsing Video
Claude cannot play video, but it can read images. To interpret a video, sample frames evenly across its duration, tile them into timestamped contact sheets, and Read the sheets. A 4×4 sheet compresses ~16 moments into one image, preserving narrative flow — what changed, in what order, roughly when.
Requires ffmpeg/ffprobe (apt-get update && apt-get install -y ffmpeg if missing).
Workflow
1. Probe first
ffprobe -v quiet -print_format json -show_format -show_streams input.mp4
Note duration, resolution, and whether there's an audio stream. Duration drives how many sheets you need.
2. Generate contact sheet(s)
python3 scripts/contact_sheet.py input.mp4 # 1 sheet, 4x4, whole video
python3 scripts/contact_sheet.py input.mp4 --sheets 3 # 48 frames across 3 sheets
python3 scripts/contact_sheet.py input.mp4 --start 120 --end 300 # zoom into 2:00–5:00
python3 scripts/contact_sheet.py input.mp4 --grid 3x3 --tile-width 500 # fewer, larger tiles
The script probes duration, samples frames at interval midpoints, stamps each tile with its source timestamp (H:MM:SS, bottom-left), and tiles them into <name>_sheet_NN.png. It prints each sheet's time range.
Sheet budget — more sheets = more Read calls; scale to duration and task:
| Duration | Sheets | Sampling interval |
|---|---|---|
| < 2 min | 1 (4×4) | ~4–7 s |
| 2–10 min | 2–4 | ~10–40 s |
| 10–60 min | 4–8, or coarse-then-zoom | ~1–2 min |
| > 1 hour | coarse pass, then zoom | varies |
3. Read and interpret
Read each sheet image. Tiles run left-to-right, top-to-bottom in time order; use the stamped timestamps to anchor observations ("the scene changes around 1:42"). Cross-sheet continuity: the last tile of sheet N immediately precedes the first tile of sheet N+1.
4. Zoom when needed
Contact sheets trade resolution for coverage. When something needs a closer look:
# Re-sheet a narrower window at higher tile resolution
python3 scripts/contact_sheet.py input.mp4 --start 95 --end 125 --grid 3x3 --tile-width 500
# Or extract a single full-resolution frame at the moment of interest
ffmpeg -ss 00:01:42 -i input.mp4 -frames:v 1 detail.png
What ships with it
4 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.
- 8d ago First seen · 144 lines · 160 tokens per session scan A c7a5f2be5243
parsing-video is a skill published in the GitHub repository oaustegard/claude-skills (148 stars, last pushed yesterday), licensed MIT. It adds 160 tokens to every session and 2,247 once invoked, about $0.0008 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.
Other skills, from other repositories
superdesign
Design or redesign frontend UI, presentations, and graphics on the Superdesign canvas with a choice of leading AI models. Use whenever the user wants to design a page, feature, flow, slide deck, or brand-new product; improve or reproduce existing UI; compare design results across top models; explore visual variants…
high-quality-slides
A method for creating polished presentation slides, including HTML slide decks, with research, a clear story, chosen visuals, and fixed layouts.
sora2
An Sora2 content-creation and work-analysis tool for finding works, users, comments, remixes, downloads, and media information, as well as uploading images and creating videos. Sora2 is a video-generation service.
remotion-performance-optimizer
Analyzes Remotion compositions for performance issues and provides optimization recommendations. Identifies expensive computations, unnecessary re-renders, large assets, memoization opportunities, and architecture improvements. Use when optimizing render times or when asked to "improve performance", "speed up…
remotion-asset-coordinator
Bridges asset requirements from motion design specs to production-ready assets. Parses specs for required assets, recommends free/paid sources, provides format conversion guidance, generates validated import code, and offers asset preparation checklists. Use when preparing assets for Remotion projects or when asked…
remotion-video-reviewer
Structured review process for Remotion video implementations. Analyzes spec compliance, detects common timing/easing issues, validates asset quality, and provides prioritized revision lists. Use when reviewing Remotion code against design specs or performing quality assurance on video compositions. Trigger phrases…