SKILLEMALL.ai

BA figma-pixel

Figma-to-frontend visual QA workflow for building pages from Figma designs and tightening existing implementations. Captures the target page, exports the selected Figma frame, runs pixel and layout comparisons, and produces local reports that guide spacing, typography, color, and structure fixes. Use when a user provides a Figma URL and asks to build, recreate, compare, match, restyle, or improve a web UI.

ClawHub Agent Skills author: valerii-baidak v1.0.14 MIT-0 41 files body ≈ 6 595 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process A 81/100 · Runs to the end — weak spots: progress reporting

ProcedureFigmaDesigntype and topics are labelled automatically from the skill text
JSON
Technical rating
B
87/100
safety, quality, tests
Safety 60%
94
Quality 40%
76
Run on models
none yet
Process rating
A
81/100
Runs to the end
Progress reporting w 2
0
When it triggers w 12
50
Result and completion w 14
60
the three weakest of ten parameters · all ten

What is at stake

Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.

Broad scope medium severity

Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.

If you install

The skill asks for more than the task needs: broad tool access, credential environment variables, binaries. Every extra permission widens the damage from a mistake or a compromise.

For the author

Narrow allowed-tools and the variable list to the minimum; replace binaries with readable sources or scripts.

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 · 2

✓ No critical or high findings

Medium and low: 2
  • medium Broad scope meta-broad-allowed-tools SKILL.md:1
    Broad tool permissions pre-approved: Bash
    allowed-tools: Read Write Edit Bash Glob Grep
  • low Dangerous commands cmd-privilege lib/page-render.cjs:105
    Privilege escalation / world-writable permissions (detector / deny-list definition; string literal in code, not executed)
    args: ['--no-sandbox', '--disable-setuid-sandbox', '--disable-dev-shm-usage', '--disable-gpu'],
    detectorcode literal

Files scanned: 41. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning body-long SKILL.md body ≈ 6595 tokens (recommended < 5000); move details to references/

Process rating: all ten parameters 81/100

  • 0Progress reporting. Says nothing while it works
  • 50When it triggers. No condition that starts the skill
  • 60Result and completion. Output format stated, no completion criterion
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 70Execution cost. Instruction body is 6595 tokens
  • 100Tools and files. Tools declared in frontmatter
  • 100Steps. 121 steps
  • 100Failures and branches. 11 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 17 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)
  • -5TODO / placeholder text left in the skill
  • +1No license
  • +2Single-language instructions
  • +3Description length 409: enough signal without eating the budget
  • +4Structure: 18 headings
  • +3Step-by-step instructions: 121 items
  • +3Output format is stated explicitly
  • +4Has examples (6 code blocks)
  • +4Reference files are cited in the instructions (5 of 6)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 76.

External checks

ClawHub: clean
This is a disclosed Figma visual QA skill whose token use, browser rendering, local artifacts, and frontend edits fit its stated purpose.
LLM: benign (high) · VirusTotal: · 29 May 2026