SKILLEMALL.ai

AC video-editor

JSON template-driven video rendering engine with multi-layer compositing (z_index stacking), entrance/exit effects (slide_in/zoom_in/fade), continuous animations (ken_burns/pan/pulse), three-track audio (narration/BGM/SFX), deep subtitle binding and style overrides. Use this skill when rendering a JSON project template into a video.

ClawHub Agent Skills author: www v1.0.0 MIT-0 12 files body ≈ 1 666 tokens Open the sourceclawhub.ai analyzed 11 h ago

JSON template-driven video rendering engine with multi-layer compositing (zindex stacking), entrance/exit effects (slidein/zoomin/fade), continuous animations…

As a process C 51/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

GeneratorMedia and videotype and topics are labelled automatically from the skill text
JSON
Technical rating
A
90/100
safety, quality, tests
Safety 60%
100
Quality 40%
75
Run on models
none yet
Process rating
C
51/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
0
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: 12. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • warning frontmatter-yaml SKILL.md: the frontmatter is not valid YAML (YAML parse error: Nested mappings are not allowed in compact mappings at line 3, column 16: compatibility: Requires Python 3.9+, install dependencies: pip install moviepy … ^ ); fields were read line by line. The usual cause is a colon inside an unquoted value

    Process rating: all ten parameters 51/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Failures and branches. Linear process with no failure handling
    • 0Progress reporting. Says nothing while it works
    • 20When it triggers. No condition that starts the skill
    • 85Steps. 7 steps, 1 vague phrases
    • 100Tools and files. Tools declared in frontmatter
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1666 tokens
    • 100Running it twice. No mutating operations

    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
    • -36 of 7 scripts are never mentioned in SKILL.md
    • +1No license
    • +2Single-language instructions
    • +3Description length 334: enough signal without eating the budget
    • +4Structure: 17 headings
    • +3Step-by-step instructions: 7 items
    • +4Has examples (13 code blocks)
    • +4Reference files are cited in the instructions (1 of 2)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 75.

    External checks

    ClawHub: clean
    This appears to be a local video-rendering tool whose behavior matches its purpose, with ordinary cautions about nearby .env files and output overwrites.
    LLM: benign (high) · VirusTotal: · 26 Jun 2026