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 VectorPeak/vectorpeak-agent-skills --skill gif-showcase-maker-vpgit clone --depth 1 https://github.com/VectorPeak/vectorpeak-agent-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/vectorpeak/vectorpeak-agent-skills/gif-showcase-maker-vp)<a href="https://agentmods.dev/skills/vectorpeak/vectorpeak-agent-skills/gif-showcase-maker-vp"><img src="https://agentmods.dev/badge/skills/vectorpeak/vectorpeak-agent-skills/gif-showcase-maker-vp/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/vectorpeak/vectorpeak-agent-skills/gif-showcase-maker-vp"><img src="https://agentmods.dev/badge/skills/vectorpeak/vectorpeak-agent-skills/gif-showcase-maker-vp.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 | $0.00073 | $0.00864 |
| Opus 5 | $0.00036 | $0.00432 |
| Sonnet 5 | $0.00015 | $0.00173 |
| Haiku 4.5 | $0.00007 | $0.00086 |
Grade A, and why
gif-showcase-maker-vp 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 10d 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 — 115 lines — stays where its author put it; the contents beside it link to each section on GitHub.
GIF Showcase Maker
Purpose
Generate a lightweight GIF from multiple images. The default mode is a simple ordered carousel:
image 1 hold -> fade to image 2 -> image 2 hold -> fade to image 3 -> image 3 hold
Use this skill for README demos, product screenshots, feature introductions, visual changelogs, and quick image-sequence previews.
Dependency
The script requires Pillow:
pip install pillow
Use Python 3.10 or newer.
Do not add heavy video dependencies unless the user asks for MP4/WebP or advanced effects.
Default Behavior
When the user provides image attachments or local image paths, those user-provided images are the required input. Do not replace them with generated placeholder images. Use generated test images only when the user explicitly asks for a reproducible self-test or when no user images are available and the response clearly says it is only a test.
If the user does not specify parameters, use:
order: input/upload order
fps: 12
hold-ms: 900
fade-ms: 450
fit: contain
background: #ffffff
loop: 0
output: showcase.gif
The default output should be written under the current project or a temporary output folder, not into a hardcoded personal path.
For this repository layout, prefer writing generated GIFs under the skill folder's output/ directory, for example knowledge-skills/gif-showcase-maker-vp/output/user-showcase.gif.
Workflow
- Identify the input image files and preserve the user's order unless they provide an explicit order.
- Choose a canvas size:
- Use
--width/--heightif provided - Otherwise use the first image size
- Use
- Resize every image into the canvas with
fit=containby default. - Add hold frames for each image.
- Add cross-fade transition frames between adjacent images.
- Save a looping GIF.
- Verify that the output file exists, has multiple frames, expected dimensions, and visible frame changes.
- Open the folder that contains the generated GIF in Windows File Explorer so the user can immediately inspect the output file. Prefer opening the skill-internal
output/folder when using this skill in a repository. - Return the GIF path and, when supported, embed the generated GIF with Markdown image syntax in the final answer.
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.
- 10d ago First seen · 115 lines · 73 tokens per session scan A 20725866d30a
gif-showcase-maker-vp is a skill published in the GitHub repository VectorPeak/vectorpeak-agent-skills (2 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 73 tokens to every session and 864 once invoked, about $0.0004 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 2026-08-31.
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