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 skills/0xdarkmatter/claude-mods/ffmpeg-opsnpx skills add 0xDarkMatter/claude-mods --skill ffmpeg-opsgit clone --depth 1 https://github.com/0xDarkMatter/claude-modsWrote 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/0xdarkmatter/claude-mods/ffmpeg-ops)<a href="https://agentmods.dev/skills/0xdarkmatter/claude-mods/ffmpeg-ops"><img src="https://agentmods.dev/badge/skills/0xdarkmatter/claude-mods/ffmpeg-ops.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 5.1 | $0.00078 | $0.08082 |
| Opus 5 | $0.00039 | $0.04041 |
| Sonnet 5 | $0.00016 | $0.01616 |
| Haiku 4.5 | $0.00008 | $0.00808 |
Grade A, and why
ffmpeg-ops 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 6d 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.
This is a copy
86% identical to quality-grading — 632 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 511 lines — stays where its author put it; the contents beside it link to each section on GitHub.
ffmpeg Operations
Operational expertise for ffmpeg/ffprobe: the ~30 commands that cover most real work, the footguns that silently ruin output, EDL-driven editing (edit-as-code), and eight scripts that replace the logic an agent would otherwise re-derive every task.
Doctrine: probe first
Never transcode, cut, or filter blind. Every media task starts by probing the input — codec, duration, frame rate (constant or variable?), pixel format, rotation, stream layout. Half of all "ffmpeg did something weird" reports are a property of the input the command never checked.
python skills/ffmpeg-ops/scripts/probe-media.py input.mp4 # human summary
python skills/ffmpeg-ops/scripts/probe-media.py --doctor input.mp4 # TRIAGE: hazards + exact fixes
python skills/ffmpeg-ops/scripts/probe-media.py --json input.mp4 | jq '.data.streams'
python skills/ffmpeg-ops/scripts/probe-media.py --keyframes-near 92.5 input.mp4
--doctor makes the doctrine self-enforcing: VFR, HDR transfer, rotation
metadata, interlacing, non-yuv420p delivery, and moov-at-EOF each come back as a
finding with the exact fix command, and exit 10 means "fix before processing".
The --keyframes-near form answers "can I stream-copy a cut at 92.5s?" — it
reports the nearest keyframes so you know whether a copy cut will snap (see
Footguns). When a command fails with a cryptic message, decode it:
references/error-decoder.md.
Before recommending an encoder, verify the build has it. Installed ffmpeg builds vary wildly (especially hardware encoders — listed ≠ working):
bash skills/ffmpeg-ops/scripts/capability-scan.sh # full: proof-encodes each hw encoder
bash skills/ffmpeg-ops/scripts/capability-scan.sh --quick # list-only, no GPU touch
Cookbook
Commands are bash-form; they run unchanged in PowerShell except where the
Windows notes say otherwise. Replace -y/-n (overwrite/never)
consciously — never leave an agent-run command interactive.
What ships with it
34 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.
- assets/edl-schema.json 2.9 KB
- assets/encoding-presets.json 3.7 KB
- assets/hls-ladder.json 1.6 KB
- references/analysis-validation.md 3.4 KB
- references/audio.md 3.4 KB
- references/capture-devices.md 2.8 KB
- references/color-grading.md 4.2 KB
- references/color-hdr.md 3.1 KB
- references/edit-as-code.md 3.9 KB
- references/encoding.md 4.0 KB
- references/error-decoder.md 7.1 KB
- references/filtergraph.md 3.4 KB
- references/hardware-accel.md 3.2 KB
- references/images-gif.md 3.8 KB
- references/look-recipes.md 18 KB
- references/quality-metrics.md 3.1 KB
- references/restoration.md 2.7 KB
- references/streaming-hls.md 2.9 KB
- references/stt-whisper.md 3.9 KB
- references/subtitles.md 2.6 KB
- references/trim-concat.md 4.1 KB
- references/visualization.md 3.2 KB
- scripts/capability-scan.sh 5.9 KB runs code
- scripts/cut-from-edl.py 11 KB runs code
- scripts/detect-segments.py 7.7 KB runs code
- scripts/gen-luts.py 15 KB runs code
- scripts/loudnorm-scan.py 5.2 KB runs code
- scripts/make-chapters.py 11 KB runs code
- scripts/make-sprites.py 6.5 KB runs code
- scripts/probe-media.py 14 KB runs code
- scripts/quality-compare.py 8.7 KB runs code
- scripts/smart-compress.py 10 KB runs code
- scripts/verify-commands.sh 6.9 KB runs code
- tests/run.sh 16 KB runs code
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.
- 6d ago First seen · 511 lines · 78 tokens per session scan A c0b2b847b6b0
ffmpeg-ops is a skill published in the GitHub repository 0xDarkMatter/claude-mods (32 stars, last pushed 13d ago), licensed MIT. It adds 78 tokens to every session and 8,082 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. It is 86% identical to quality-grading, differing in 632 lines, and is treated as a copy.
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