SKILLEMALL.ai

AC picasso

The ultimate frontend design and UI engineering skill. Use this whenever the user asks to build, design, style, or improve any web interface, component, page, application, dashboard, landing page, artifact, poster, or visual output. Covers typography, color systems, spatial design, motion/animation, interaction design, responsive layouts, sound design, haptic feedback, icon systems, generative art, theming, React best practices, and DESIGN.md system generation. Also use when the user asks to audit, critique, polish, simplify, animate, or normalize a frontend. Triggers on any mention of "make it look good," "fix the design," "UI," "UX," "frontend," "component," "landing page," "dashboard," "artifact," "poster," "design system," "theme," "animation," "responsive," or any request to improve visual quality. Use this skill even when the user does not explicitly ask for design help but the task involves producing a visual interface.

ClawHub Agent Skills author: Viperr v2.0.3 MIT-0 34 files body ≈ 5 873 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process C 63/100 · Has gaps — weak spots: result and completion, inputs and preconditions, running it twice

AnalyzerSoftware developmentDesignMarketingtype and topics are labelled automatically from the skill text
JSON
Technical rating
A
92/100
safety, quality, tests
Safety 60%
100
Quality 40%
80
Run on models
none yet
Process rating
C
63/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Running it twice w 4
30
the three weakest of ten parameters · all ten

How to improve

  1. The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
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: 34. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning body-long SKILL.md body ≈ 5873 tokens (recommended < 5000); move details to references/

Process rating: all ten parameters 63/100

  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 30Running it twice. 17 mutating operations with no state check
  • 60Tools and files. Uses tools (bash) that frontmatter does not declare
  • 70Execution cost. Instruction body is 5873 tokens
  • 100Steps. 66 steps
  • 100When it triggers. States when to use and when not to
  • 100Failures and branches. 9 branches, has a failure section
  • 100Consistency. Name and required fields are in place
  • 100Progress reporting. Reports progress
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • low 14 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

  • +4Description does not say when NOT to use the skill (false activations)
  • +3Description length 940: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • +1No license
  • +2Single-language instructions
  • +5Description quotes 12 example trigger phrases
  • +4Structure: 29 headings
  • +3Step-by-step instructions: 66 items
  • +4Has examples (1 code blocks)
  • +4Reference files are cited in the instructions (32 of 32)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 80.

External checks

ClawHub: clean
This is a frontend design guidance skill with broad but disclosed scope and no executable install or hidden data behavior.
LLM: benign (high) · VirusTotal: · 29 May 2026