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 nicepkg/ai-workflow --skill video-to-gifgit clone --depth 1 https://github.com/nicepkg/ai-workflowWrote 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/nicepkg/ai-workflow/video-to-gif)<a href="https://agentmods.dev/skills/nicepkg/ai-workflow/video-to-gif"><img src="https://agentmods.dev/badge/skills/nicepkg/ai-workflow/video-to-gif/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/nicepkg/ai-workflow/video-to-gif"><img src="https://agentmods.dev/badge/skills/nicepkg/ai-workflow/video-to-gif.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 | $0.00039 | $0.02318 |
| Opus 5 | $0.00019 | $0.01159 |
| Sonnet 5 | $0.00008 | $0.00464 |
| Haiku 4.5 | $0.00004 | $0.00232 |
Grade A, and why
video-to-gif 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 5d 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 — 371 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Video to GIF Workshop
Transform video clips into high-quality, optimized GIFs perfect for social media, documentation, tutorials, and presentations. Features precise timing control, text overlays, effects, and intelligent file size optimization.
Core Capabilities
- Clip Selection: Extract specific time ranges from videos
- Speed Control: Slow motion, speed up, or reverse
- Cropping: Resize and crop to any dimensions
- Text Overlays: Add captions, titles, or watermarks
- Effects: Filters, fades, color adjustments
- Optimization: Smart compression for target file size
- Batch Processing: Convert multiple clips at once
Quick Start
from scripts.gif_workshop import GifWorkshop
# Basic conversion
workshop = GifWorkshop("video.mp4")
workshop.to_gif("output.gif")
# With options
workshop = GifWorkshop("video.mp4")
workshop.clip(start=5, end=10) # 5-10 seconds
workshop.resize(width=480) # Resize to 480px wide
workshop.set_fps(15) # 15 frames per second
workshop.optimize(max_size_kb=500) # Max 500KB
workshop.to_gif("output.gif")
Core Workflow
1. Load Video
from scripts.gif_workshop import GifWorkshop
# From file
workshop = GifWorkshop("video.mp4")
# With initial settings
workshop = GifWorkshop("video.mp4", fps=15, width=480)
2. Select Clip Range
# By time (seconds)
workshop.clip(start=5, end=15) # 5s to 15s
# By time string
workshop.clip(start="00:01:30", end="00:01:45") # 1:30 to 1:45
# From start or to end
workshop.clip(start=10) # From 10s to end
workshop.clip(end=5) # First 5 seconds
# Multiple clips
workshop.clip_multi([
(0, 3),
(10, 15),
(20, 25)
]) # Concatenates clips
3. Adjust Speed
# Speed up
workshop.speed(2.0) # 2x faster
# Slow motion
workshop.speed(0.5) # Half speed
# Reverse
workshop.reverse()
# Boomerang effect (forward then reverse)
workshop.boomerang()
4. Resize and Crop
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.
- 5d ago First seen · 371 lines · 39 tokens per session scan A ef6fd39845d5
video-to-gif is a skill published in the GitHub repository nicepkg/ai-workflow (282 stars, last pushed 7mo ago), licensed MIT. It adds 39 tokens to every session and 2,318 once invoked, about $0.0002 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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