SKILLEMALL.ai

AC Art

Static visual content in 20+ formats (diagrams, infographics, comics, icons, wallpaper) via Nano Banana Pro by default, Nano Banana, and Flux, plus technical diagrams and a few essay illustrations that draw themselves as looping GIFs. USE WHEN art, illustration, diagram, flowchart, animated diagram, diagram GIF, animated essay image, animated header, infographic, header image, blog social thumbnail, generate image, mermaid, comic, icon, blog art, framework diagram, D3 chart, remove background, wallpaper. NOT FOR any request that says visualize (Visualize owns every "visualize X" and may embed Art output), YouTube/video thumbnails (the video skill), other video or animation (HyperFrames), web UI design (Webdesign).

danielmiessler/Personal_AI_Infrastructure Agent Skills author: danielmiessler MIT 46 files · 6 scripts body ≈ 4 835 tokens Open the sourcegithub.com↗ analyzed 28 h ago

Static visual content in 20+ formats (diagrams, infographics, comics, icons, wallpaper) via Nano Banana Pro by default, Nano Banana, and Flux, plus technical…

As a process C 54/100 · Has gaps — weak spots: inputs and preconditions, failures and branches, running it twice

GeneratorYouTubeMedia and videoDesigntype and topics are labelled automatically from the skill text
JSON
Technical rating
A
96/100
safety, quality, tests
Safety 60%
100
Quality 40%
89
Run on models
none yet
Process rating
C
54/100
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: 45. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • warning name-format name should be kebab-case (lowercase letters, digits, hyphens)
    • note frontmatter-key unknown frontmatter key "evals"

    Process rating: all ten parameters 54/100

    • 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
    • 30Running it twice. 19 mutating operations with no state check
    • 50When it triggers. No condition that starts the skill
    • 60Tools and files. Uses tools (bash) that frontmatter does not declare
    • 60Result and completion. Output format stated, no completion criterion
    • 70Execution cost. Instruction body is 4835 tokens
    • 100Steps. 27 steps
    • 100Consistency. Name and required fields are in place
    • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
    • low The response is described with custom markup (14 tags): a typed call is more reliable

    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
    • +1No license
    • +2Single-language instructions
    • +4Description says when NOT to use the skill
    • +3Description length 723: enough signal without eating the budget
    • +4Structure: 12 headings
    • +3Step-by-step instructions: 27 items
    • +3Output format is stated explicitly
    • +4Has examples (4 code blocks)
    • +4Reference files are cited in the instructions (4 of 4)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 89.