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AC video-to-gif

Convert video files or clips into animated GIFs/WebP using ffmpeg, with resizing, fps control, trimming, palette generation, and file-size optimization. Use when the user asks to turn video into GIF/动图, make a GIF from mp4/mov/webm/mkv, extract a video segment as an animation, compress an animated GIF, or create a shareable short looping animation.

ClawHub Agent Skills author: xiwei26 v1.0.0 MIT-0 3 files body ≈ 480 tokens Open the sourceclawhub.ai↗ analyzed 4 d ago

As a process C 56/100 · Has gaps — weak spots: result and completion, inputs and preconditions, consistency

GeneratorMedia and videotype and topics are labelled automatically from the skill text
Runs in: OpenClaw Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) Goose OpenCode
JSON
Technical rating
A
95/100
safety, quality, tests
Safety 60%
100
Quality 40%
87
Run on models
none yet
Process rating
C
56/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Consistency w 8
40
the three weakest of ten parameters · all ten

How to improve

    For the model run — optional
    • Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
    • A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.

    Guard findings · 0

    ✓ No critical or high findings

    Files scanned: 3. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    ✓ No remarks against the Agent Skills spec

    Process rating: all ten parameters 56/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 40Consistency. Frontmatter name (video-to-gif) differs from the folder (video-to-gif-hq)
    • 60Tools and files. Uses tools (bash) that frontmatter does not declare
    • 70When it triggers. States when to use, but not when not to
    • 70Failures and branches. 4 branches
    • 100Steps. 21 steps
    • 100Execution cost. Instruction body is 480 tokens
    • 100Running it twice. No mutating operations
    • 100Progress reporting. Reports progress

    Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.

    Quality signals

    • +5Description has no quoted example phrases that should trigger the skill
    • +4Description does not say when NOT to use the skill (false activations)
    • +3Output format is not stated: the model decides each time
    • +1No license
    • +2Single-language instructions
    • +3Description length 350: enough signal without eating the budget
    • +4Structure: 5 headings
    • +3Step-by-step instructions: 21 items
    • +4Has examples (1 code blocks)
    • +3All 1 scripts are documented

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 87.

    External checks

    ClawHub: clean
    This skill locally converts user-provided videos to GIF or WebP and shows no evidence of hidden network, credential, persistence, or destructive behavior.
    LLM: benign (high) · VirusTotal: · 29 May 2026