SkillsBench is a benchmark for measuring how effectively AI agents use modular skills—folders containing instructions, scripts, and resources—to complete specialized tasks. It helps researchers and developers evaluate both skill quality and agent behavior, including tasks that require combining multiple skills. The catalogue’s skills and instructions are evaluated as part of this workflow.
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 benchflow-ai/skillsbench --skill ffmpeg-keyframe-extractiongit clone --depth 1 https://github.com/benchflow-ai/skillsbenchWrote 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/benchflow-ai/skillsbench/ffmpeg-keyframe-extraction)<a href="https://agentmods.dev/skills/benchflow-ai/skillsbench/ffmpeg-keyframe-extraction"><img src="https://agentmods.dev/badge/skills/benchflow-ai/skillsbench/ffmpeg-keyframe-extraction/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/benchflow-ai/skillsbench/ffmpeg-keyframe-extraction"><img src="https://agentmods.dev/badge/skills/benchflow-ai/skillsbench/ffmpeg-keyframe-extraction.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 | $0.00064 | $0.00558 |
| Opus 5 | $0.00032 | $0.00279 |
| Sonnet 5 | $0.00013 | $0.00112 |
| Haiku 4.5 | $0.00006 | $0.00056 |
Grade A, and why
ffmpeg-keyframe-extraction 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- ffmpeg-keyframe-extraction — 100% identical, 0 lines differ
What it actually says
FFmpeg Keyframe Extraction
Extract key frames (I-frames) from video files using FFmpeg CLI.
Prerequisites
- FFmpeg installed and available in PATH
- Input video file (MP4, MKV, AVI, MOV, etc.)
Methods
Method 1: Select Filter (More Control)
ffmpeg -i <input_video> -vf "select='eq(pict_type,I)'" -vsync vfr <output_pattern>
Method 2: Skip Frame (Faster)
ffmpeg -skip_frame nokey -i <input_video> -vsync vfr <output_pattern>
Key Options
Option Description
-i <file> Input video file
-vf "select='eq(pict_type,I)'" Filter selecting only I-frames
-skip_frame nokey Skip decoding non-keyframes (performance)
-vsync vfr Variable frame rate, prevents duplicates
-q:v <n> Quality (1-31, lower = better, for JPEG)
-frame_pts 1 Use presentation timestamp in filename
Output Patterns
frame_%03d.png - PNG sequence (frame_001.png, frame_002.png...)
frame_%03d.jpg - JPEG sequence
frame_%d.bmp - BMP sequence
Examples
Basic PNG extraction:
ffmpeg -i video.mp4 -vf "select='eq(pict_type,I)'" -vsync vfr keyframe_%03d.png High-quality JPEG:
ffmpeg -i video.mp4 -skip_frame nokey -vsync vfr -q:v 2 keyframe_%03d.jpg With timestamps:
ffmpeg -i video.mp4 -vf "select='eq(pict_type,I)'" -vsync vfr -frame_pts 1 keyframe_%d.png
To specific directory:
ffmpeg -i video.mp4 -vf "select='eq(pict_type,I)'" -vsync vfr ./output/keyframe_%03d.png
## Notes
Method 2 (-skip_frame nokey) is faster as it skips decoding non-keyframes
Method 1 offers more filtering flexibility (can combine with other filters)
Keyframe frequency depends on video encoding settings
Use -vsync vfr to avoid duplicate frames in output
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 · 64 lines · 64 tokens per session scan A 67d169e60ca7
ffmpeg-keyframe-extraction is a skill published in the GitHub repository benchflow-ai/skillsbench (1,764 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 64 tokens to every session and 558 once invoked, about $0.0003 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.
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