AB nielsen-ui-review
Run a structured UI/UX heuristic review based on Nielsen's 10 usability principles for screenshots, mockups, wireframes, product pages, app screens, and design comps. Use when the user provides a UI image or screen and asks to review, critique, evaluate, audit, or assess the interface, usability, UX, or design quality, including requests such as "review this UI", "evaluate this interface", "do a heuristic evaluation", "give me UI feedback", "assess usability", or Chinese requests like "评价一下这个界面", "帮我做 UI 评审", or "做个可用性分析". Ask a short clarification round first, using selectable options when possible, then generate prioritized findings and actionable recommendations.
As a process B 68/100 · Nearly there — weak spots: inputs and preconditions, consistency, progress reporting
How to improve
- 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: 2. 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 68/100
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Progress reporting. Says nothing while it works
- 40Consistency. Frontmatter name (nielsen-ui-review) differs from the folder (ui-review)
- 60Result and completion. Output format stated, no completion criterion
- 70When it triggers. States when to use, but not when not to
- 70Failures and branches. 7 branches
- 85Steps. 155 steps, 1 vague phrases
- 100Tools and files. No external tools needed
- 100Execution cost. Instruction body is 2095 tokens
- 100Running it twice. Mutating operations check current state
- low 12 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)
- +4No input/output examples
- +1No license
- +2Single-language instructions
- +5Description quotes 8 example trigger phrases
- +3Description length 674: enough signal without eating the budget
- +4Structure: 21 headings
- +3Step-by-step instructions: 155 items
- +3Output format is stated explicitly
Quality base 70; lint remarks subtract, signals add up to 100. Result: 88.