SKILLEMALL.ai

AC h3-prompt-writing

Write MiniMax H3 video generation prompts for T2VA, I2VA, FL2VA, L2VA, and Ref2VA. Use when rewriting multimodal requests into H3 prompt structures, composing integrated_multimodal_description, overall_soundscape, and non_diegetic_music, aligning keyframes, or defining reference labels for images, videos, and audio.

The skillemall take

A skill for MiniMax H3 video generation: converts text requests into structured prompts for five modes (T2VA, I2VA, and others). Promises to handle integrated multimodal descriptions, soundscapes, and reference frames.

Files contain 499 tokens of instructions across three files with no critical errors. Safety and quality score 100 and 87 respectively, but process score sits at 57—a hint of execution gaps. No critical or medium findings. Designed for ComfyUI integration and supported across major platforms from Claude to DeepSeek.

Install if you need H3-prompt structuring for video generation. Otherwise, don't expect miracles: the process runs at half throttle.

hradec/ComfyUI-HR-Endless-Sampler Agent Skills author: hradec 3 files body ≈ 499 tokens Open the sourcegithub.com↗ analyzed 10 h ago

Write MiniMax H3 video generation prompts for T2VA, I2VA, FL2VA, L2VA, and Ref2VA.

As a process C 57/100 · Has gaps — weak spots: when it triggers, inputs and preconditions, failures and branches

GeneratorAI and agentsMedia and videotype and topics are labelled automatically from the skill text
JSON
Technical rating
A
95/100
safety, quality, tests
Safety 60%
100
Quality 40%
87
Run on models
none yet
Process rating
C
57/100
Has gaps
Inputs and preconditions w 11
0
Failures and branches w 10
0
Progress reporting w 2
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: 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 57/100

    • 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
    • 40Consistency. Frontmatter name (h3-prompt-writing) differs from the folder (minimax-h3-prompt-writing)
    • 60Result and completion. Output format stated, no completion criterion
    • 100Tools and files. No external tools needed
    • 100Steps. 15 steps
    • 100Execution cost. Instruction body is 499 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)
    • +4No input/output examples
    • +1No license
    • +2Single-language instructions
    • +3Description length 317: enough signal without eating the budget
    • +4Structure: 6 headings
    • +3Step-by-step instructions: 15 items
    • +3Output format is stated explicitly
    • +4Reference files are cited in the instructions (2 of 2)

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