SKILLEMALL.ai
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BB canvas-design

These are instructions for creating design philosophies - aesthetic movements that are then EXPRESSED VISUALLY. Output only .md files, .pdf files, and .png files.

The skillemall take

The skill generates design philosophies and outputs them as documents and images. Promises to create aesthetic movements with visual expression, but in practice works simpler: produces markdown, PDF, and PNG from text instructions.

Tests show a B grade with 81 percent quality score. No critical bugs found, links intact, files present. Models weren't run, sandbox wasn't tested—so actual behavior on your machine remains unclear. Compatible with all major platforms from Claude to DeepSeek.

Install if you need a quick visual concept generator for boards or presentations. Skip it if you expect something more complex than nicely formatted ideas.

sickn33/agentic-awesome-skills Agent Skills author: sickn33 MIT 29 files body ≈ 3 342 tokens Open the sourcegithub.com↗ analyzed 5 d ago

These are instructions for creating design philosophies - aesthetic movements that are then EXPRESSED VISUALLY.

As a process B 71/100 · Nearly there — weak spots: when it triggers, running it twice, progress reporting

GeneratorPDFDesignSoftware developmentAI and agentstype and topics are labelled automatically from the skill text
Runs in: Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) OpenClaw Goose OpenCode
JSON
Technical rating
B
94/100
safety, quality, tests
Safety 60%
100
Quality 40%
84
Run on models
none yet
Process rating
B
71/100
Nearly there
Progress reporting w 2
0
When it triggers w 12
20
Running it twice w 4
30
the three weakest of ten parameters · all ten

The same skill appears in 1 more place: agentic-awesome-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: 29. 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 71/100

    • 0Progress reporting. Says nothing while it works
    • 20When it triggers. No condition that starts the skill
    • 30Running it twice. 15 mutating operations with no state check
    • 55Failures and branches. 1 branches
    • 60Tools and files. Uses tools (web) that frontmatter does not declare
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 100Steps. 29 steps
    • 100Result and completion. Output format and completion criterion are stated
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 3342 tokens
    • 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)
    • +4No input/output examples
    • +2Single-language instructions
    • +3Description length 162: enough signal without eating the budget
    • +4Structure: 12 headings
    • +3Step-by-step instructions: 29 items
    • +3Output format is stated explicitly
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 84.