SKILLEMALL.ai

AF figma-to-static

Convert Figma design files to pixel-level mobile-first static HTML/CSS pages. Use when: (1) user provides a Figma file link and wants a static web page, (2) user sends design screenshots/assets and says "按设计图还原", (3) user asks to build a landing page from Figma, (4) iterating on Figma-to-code pixel accuracy. Handles: Figma MCP-first extraction (metadata/context/screenshots) with REST API fallback, layered DOM reconstruction (not whole-image paste), visual diff pipeline with region heatmap for quality validation, mobile-first responsive layout. NOT for: React/Vue/SPA frameworks, server-side rendering, interactive JS-heavy pages.

ClawHub Agent Skills author: kent v2.0.6 MIT-0 21 files · 1 script body ≈ 6 887 tokens Open the sourceclawhub.ai analyzed 2 d ago

As a process F 47/100 · Will not run — References files that are not bundled: assets/*

GeneratorFigmaDesigntype and topics are labelled automatically from the skill text
JSON
Technical rating
A
91/100
safety, quality, tests
Safety 60%
100
Quality 40%
77
Run on models
none yet
Process rating
F
47/100
Will not run
References files that are not bundled: assets/*
Tools and files w 18
0
Result and completion w 14
0
Inputs and preconditions w 11
0
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.
  2. The text references files that are not there: add them or drop the references.
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: 21. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning body-long SKILL.md body ≈ 6887 tokens (recommended < 5000); move details to references/
  • warning missing-ref reference to a missing file: assets/*

Process rating: all ten parameters 47/100

Will not run. References files that are not bundled: assets/*
  • 0Tools and files. 1 referenced file(s) missing: assets/*
  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 50When it triggers. No condition that starts the skill
  • 70Execution cost. Instruction body is 6887 tokens
  • 85Steps. 223 steps, 1 vague phrases
  • 100Failures and branches. 21 branches, has a failure section
  • 100Consistency. Name and required fields are in place
  • 100Running it twice. Mutating operations check current state
  • 100Progress reporting. Reports progress
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • low 13 top-level sections: this looks like several domains in one skill
  • low The response is described with custom markup (13 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
  • +3Output format is not stated: the model decides each time
  • -2localhost URLs: will not work for another user
  • +1No license
  • +2Single-language instructions
  • +4Description says when NOT to use the skill
  • +3Description length 635: enough signal without eating the budget
  • +4Structure: 26 headings
  • +3Step-by-step instructions: 223 items
  • +4Has examples (9 code blocks)
  • +4Reference files are cited in the instructions (6 of 6)
  • +3All 12 scripts are documented

Quality base 70; lint remarks subtract, signals add up to 100. Result: 77.

External checks

ClawHub: clean
This skill is a disclosed Figma-to-HTML/CSS workflow that handles sensitive Figma and Claude authentication, so users should review the auth setup but the artifacts do not show malicious behavior.
LLM: benign (medium) · VirusTotal: · 29 May 2026