AC taste
Creative-direction layer for music videos and short-form edits in the angelcore / cloud-trance / hyperpop family — a named-genre aesthetic vocabulary, mood + color + light system, beat-synced editing grammar, and a pipeline chaining ECC's video skills from b-roll generation to distribution. Use when a video must feel intentional rather than merely functional — music videos, fancams, moodboard-driven reels, or giving AI-generated b-roll a coherent visual direction.
Promises a visual vocabulary for clips and shorts in angelcore, cloud-trance, hyperpop — mood, colors, light, beat-sync editing. Chains several ECC video skills from b-roll generation to distribution.
Files intact, no critical errors. Quality score 87 is solid for a generator. Process score 52, though, signals the logic inside isn't transparent — either docs are stripped or the pipeline relies on conventions. No model runs logged, no sandbox data.
Install if you already work with ECC and nail the mood on first attempt. Otherwise, you're betting on getting something visually coherent but unpredictable.
Creative-direction layer for music videos and short-form edits in the angelcore / cloud-trance / hyperpop family — a named-genre aesthetic vocabulary, mood +…
As a process C 52/100 · Has gaps — weak spots: result and completion, inputs and preconditions, failures and branches
How to improve
- 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: 2. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- note
frontmatter-keyunknown frontmatter key "origin"
Process rating: all ten parameters 52/100
- 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
- 30Running it twice. 13 mutating operations with no state check
- 50When it triggers. No condition that starts the skill
- 85Steps. 54 steps, 1 vague phrases
- 100Tools and files. No external tools needed
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 3704 tokens
- low 13 top-level sections: this looks like several domains in one skill
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 468: enough signal without eating the budget
- +4Structure: 17 headings
- +3Step-by-step instructions: 54 items
- +4Has examples (4 code blocks)
- +4Reference files are cited in the instructions (1 of 1)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 87.