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 processing-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/processing-video)<a href="https://agentmods.dev/skills/oaustegard/claude-skills/processing-video"><img src="https://agentmods.dev/badge/skills/oaustegard/claude-skills/processing-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/processing-video"><img src="https://agentmods.dev/badge/skills/oaustegard/claude-skills/processing-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 | $0.00239 | $0.03094 |
| Opus 5.5 | $0.00096 | $0.01238 |
| Sonnet 5.5 | $0.00048 | $0.00619 |
| Haiku 4.5 | $0.00024 | $0.00309 |
Grade A, and why
processing-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 1mo 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 — 189 lines — stays where its author put it; the contents beside it link to each section on GitHub.
ffmpeg Toolkit
ffmpeg 6.1.1 is pre-installed with a full-featured build. Also available: ffprobe (media analysis) and ffplay (playback, limited use in container).
Before writing custom Python for media tasks, check whether ffmpeg handles it in a single command.
To interpret video content (summarize, describe, find scenes) rather than transform it, use the parsing-video skill — it samples frames into timestamped contact sheets that can be read as images.
Task Reference
Probe & Inspect Media
ffprobe — always start here to understand what you're working with.
ffprobe -v quiet -print_format json -show_format -show_streams input.mp4
ffprobe -v quiet -show_entries format=duration,bit_rate -of csv=p=0 input.mp4
ffprobe -v quiet -select_streams v:0 -show_entries stream=width,height,r_frame_rate,codec_name -of csv=p=0 input.mp4
Video Format Conversion
ffmpeg -i input.avi output.mp4 # container swap (re-encode)
ffmpeg -i input.avi -c copy output.mp4 # container swap (no re-encode, fast)
ffmpeg -i input.mp4 -c:v libx265 -crf 28 output.mp4 # H.265
ffmpeg -i input.mp4 -c:v libvpx-vp9 -crf 30 -b:v 0 out.webm # VP9 WebM
ffmpeg -i input.mp4 -c:v libsvtav1 -crf 35 output.mp4 # AV1 (SVT, fastest AV1 encoder)
ffmpeg -i input.mp4 -c:v libjxl output.jxl # JPEG XL (single frame)
Encoder selection guide:
| Goal | Encoder | Typical flags |
|---|---|---|
| Compatibility | libx264 | -crf 23 -preset medium |
| Better compression | libx265 | -crf 28 -preset medium |
| Web delivery | libvpx-vp9 | -crf 30 -b:v 0 |
| Best compression | libsvtav1 | -crf 35 -preset 6 |
| Lossless archival | libx264 | -crf 0 -preset veryslow |
Lower CRF = higher quality. x264 default 23, x265 default 28, SVT-AV1 default 35 are visually similar.
Audio Format Conversion
ffmpeg -i input.wav -c:a libmp3lame -q:a 2 output.mp3 # MP3 VBR ~190kbps
ffmpeg -i input.wav -c:a libopus -b:a 128k output.opus # Opus (best quality/size)
ffmpeg -i input.wav -c:a aac -b:a 192k output.m4a # AAC
ffmpeg -i input.wav -c:a flac output.flac # FLAC lossless
ffmpeg -i input.mp3 -ar 44100 -ac 2 output.wav # to WAV, set sample rate/channels
What ships with it
2 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.
- 1mo ago First seen · 189 lines · 239 tokens per session scan A 501e1250a1c6
processing-video is a skill published in the GitHub repository oaustegard/claude-skills (157 stars, last pushed yesterday), licensed MIT. It adds 239 tokens to every session and 3,094 once invoked, about $0.0010 per session on Opus 5.5. 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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