SKILLEMALL.ai
GitHub ↗ RU Sign in

AB extract-design

Use this skill when the user wants to extract a webpage's design language into a reusable HTML style reference file, including typography, colors, spacing, surfaces, components, states, themes, motion, code-block styles, background atmosphere, decorative motifs, and art direction. The output should be a universal style specimen HTML for future AI-generated pages, not a 1:1 copy of the original page. Extracted style files are saved to the skill's own `assets/theme/` directory, never to the user's project.

LeoYeAI/openclaw-master-skills Agent Skills author: LeoYeAI MIT 15 files body ≈ 5 860 tokens Open the sourcegithub.com↗ analyzed 2 d ago

Use this skill when the user wants to extract a webpage's design language into a reusable HTML style reference file, including typography, colors, spacing…

As a process B 67/100 · Nearly there — weak spots: inputs and preconditions, progress reporting

ProcedurePlaywrightSoftware developmentDesignData and analyticstype and topics are labelled automatically from the skill text
Runs in: OpenClaw 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) Goose OpenCode
JSON
Technical rating
A
94/100
safety, quality, tests
Safety 60%
100
Quality 40%
84
Run on models
none yet
Process rating
B
67/100
Nearly there
Inputs and preconditions w 11
0
Progress reporting w 2
0
Tools and files w 18
60
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: 15. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning body-long SKILL.md body ≈ 5860 tokens (recommended < 5000); move details to references/

Process rating: all ten parameters 67/100

  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Progress reporting. Says nothing while it works
  • 60Tools and files. Uses tools (bash) that frontmatter does not declare
  • 60Result and completion. Output format stated, no completion criterion
  • 70When it triggers. States when to use, but not when not to
  • 70Execution cost. Instruction body is 5860 tokens
  • 85Steps. 350 steps, 2 vague phrases
  • 100Failures and branches. 1 branches, has a failure section
  • 100Consistency. Name and required fields are in place
  • 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
  • low 10 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)
  • +1No license
  • +2Single-language instructions
  • +3Description length 509: enough signal without eating the budget
  • +4Structure: 44 headings
  • +3Step-by-step instructions: 350 items
  • +3Output format is stated explicitly
  • +4Has examples (9 code blocks)
  • +4Reference files are cited in the instructions (1 of 1)
  • +3All 2 scripts are documented

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