SKILLEMALL.ai

AB algorithmic-art

Creating algorithmic art using p5.js with seeded randomness and interactive parameter exploration. Use this when users request creating art using code, generative art, algorithmic art, flow fields, or particle systems. Create original algorithmic art rather than copying existing artists' work to avoid copyright violations.

LeoYeAI/openclaw-master-skills Agent Skills author: LeoYeAI MIT 5 files body ≈ 4 861 tokens Open the sourcegithub.com analyzed 2 d ago

Creating algorithmic art using p5.js with seeded randomness and interactive parameter exploration. Use this when users request creating art using code…

As a process B 66/100 · Nearly there — weak spots: inputs and preconditions, consistency, progress reporting

GeneratorSoftware developmenttype and topics are labelled automatically from the skill text
JSON
Technical rating
A
95/100
safety, quality, tests
Safety 60%
100
Quality 40%
88
Run on models
none yet
Process rating
B
66/100
Nearly there
Inputs and preconditions w 11
0
Progress reporting w 2
0
Consistency w 8
40
the three weakest of ten parameters · all ten
This is a copy of a skill from another catalog; the rating counts the canonical one: algorithmic-art (LeoYeAI/openclaw-master-skills)

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: 5. 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 66/100

    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Progress reporting. Says nothing while it works
    • 40Consistency. Frontmatter name (algorithmic-art) differs from the folder (algorithmic-art-blocked)
    • 60Result and completion. Output format stated, no completion criterion
    • 70When it triggers. States when to use, but not when not to
    • 70Failures and branches. 4 branches
    • 70Execution cost. Instruction body is 4861 tokens
    • 85Steps. 128 steps, 3 vague phrases
    • 100Tools and files. No external tools needed
    • 100Running it twice. Mutating operations check current state
    • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing

    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)
    • +2Single-language instructions
    • +3Description length 324: enough signal without eating the budget
    • +4Structure: 18 headings
    • +3Step-by-step instructions: 128 items
    • +3Output format is stated explicitly
    • +4Has examples (5 code blocks)
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 88.