Install
$ agentstack add skill-vectorpeak-vectorpeak-agent-skills-gif-showcase-maker-vp ✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.
Security review
✓ PassedNo issues found. Passed automated security review. · v0.1.0 How review works →
- ✓ Prompt-injection patterns
- ✓ Secret / credential exfiltration
- ✓ Dangerous shell & filesystem operations
- ✓ Untrusted network calls
- ✓ Known-malicious package signatures
What it can access
- ✓ Network access No
- ✓ Filesystem access No
- ✓ Shell / process execution No
- ✓ Environment & secrets No
- ✓ Dynamic code execution No
From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.
Verified badge
Passed review? Show it. Paste this badge into your README, it links to the public security report.
Reliability & compatibility
Declared compatibility
Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.
We're building live execution health for every listing: tool-call success rate, median latency, uptime, and last-checked timestamps, measured, not self-reported. It isn't live yet, so we don't show numbers we can't stand behind.
How agent discovery & health will work →About
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
- 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.
Typical Commands
Minimal:
python scripts/make_sequence_gif.py --images image1.png image2.png image3.png --output showcase.gif
With timing and canvas:
python scripts/make_sequence_gif.py \
--images role.png bag.png shop.png \
--output showcase.gif \
--fps 12 \
--hold-ms 900 \
--fade-ms 450 \
--width 1200 \
--background "#dbeafe"
Verification
After generating the GIF, run a quick check:
python scripts/make_sequence_gif.py --verify showcase.gif
The check should report:
- file size
- frame count
- dimensions
- duration
- whether sampled frames differ
GIF encoders can merge identical hold frames into a single frame with a longer duration. Prefer duration, dimensions, nonzero size, and visible frame differences over exact repeated-hold frame counts.
Public Repository Rules
- Do not commit generated GIFs unless they are small intentional examples.
- Do not commit private screenshots unless the user explicitly asks.
- Do not hardcode local user paths.
- Keep dependencies in
requirements.txt. - Keep examples reproducible with generated placeholder images or documented input images.
Sync Rule
????? skill ???????????? VectorPeak/vectorpeak-agent-skills?????????????
Source & license
This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: VectorPeak
- Source: VectorPeak/vectorpeak-agent-skills
- License: Apache-2.0
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.