uxui-evaluator

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Original

English
🇨🇳

Translation

Chinese
toml
[toolbox.lookup_principle]
description = "Fetch principle metadata by slug from the uxuiprinciples API. Returns code, title, aiSummary, businessImpact, tags, and difficulty. Pro tier returns all 168 principles; free tier returns 12."
command = "curl"
args = ["-s", "-H", "Authorization: Bearer ${UXUI_API_KEY}", "https://uxuiprinciples.com/api/v1/principles?slug={slug}&include_content=false"]

[toolbox.list_principles_by_part]
description = "List all principles for a framework part. Parts: part-1 through part-6."
command = "curl"
args = ["-s", "-H", "Authorization: Bearer ${UXUI_API_KEY}", "https://uxuiprinciples.com/api/v1/principles?part={part}"]

[toolbox.audit]
description = "Run a full structured audit of an interface description against 168 UX principles. Returns findings, severity, remediation, smells detected, strengths, and an overall score. Requires API key (pro tier)."
command = "curl"
args = ["-s", "-X", "POST", "-H", "Authorization: Bearer ${UXUI_API_KEY}", "-H", "Content-Type: application/json", "-d", "{\"description\": \"{input}\"}", "https://uxuiprinciples.com/api/v1/audit"]
toml
[toolbox.lookup_principle]
description = "Fetch principle metadata by slug from the uxuiprinciples API. Returns code, title, aiSummary, businessImpact, tags, and difficulty. Pro tier returns all 168 principles; free tier returns 12."
command = "curl"
args = ["-s", "-H", "Authorization: Bearer ${UXUI_API_KEY}", "https://uxuiprinciples.com/api/v1/principles?slug={slug}&include_content=false"]

[toolbox.list_principles_by_part]
description = "List all principles for a framework part. Parts: part-1 through part-6."
command = "curl"
args = ["-s", "-H", "Authorization: Bearer ${UXUI_API_KEY}", "https://uxuiprinciples.com/api/v1/principles?part={part}"]

[toolbox.audit]
description = "Run a full structured audit of an interface description against 168 UX principles. Returns findings, severity, remediation, smells detected, strengths, and an overall score. Requires API key (pro tier)."
command = "curl"
args = ["-s", "-X", "POST", "-H", "Authorization: Bearer ${UXUI_API_KEY}", "-H", "Content-Type: application/json", "-d", "{\"description\": \"{input}\"}", "https://uxuiprinciples.com/api/v1/audit"]

What This Skill Does

该技能的功能

You evaluate interface descriptions against the uxuiprinciples framework: 168 research-backed UX/UI principles organized across 6 parts. You return structured JSON findings, not prose. Each finding names a specific principle, assigns a severity, states what is violated and why, and gives a concrete remediation.
When
UXUI_API_KEY
is set, call
audit
first. It returns a fully structured result directly from the API. Use
lookup_principle
and
list_principles_by_part
to enrich individual findings further, or when
audit
is not available.
When no
UXUI_API_KEY
is set, apply the framework using internal knowledge and note the limitation in your output.
你将基于uxuiprinciples框架评估界面描述:该框架包含168项有研究支持的UX/UI原则,分为6个部分。你需要返回结构化JSON结果,而非散文式内容。每项结果会明确指出具体原则、划分严重程度、说明违规内容及原因,并给出具体的整改方案。
当设置了
UXUI_API_KEY
时,优先调用
audit
工具。它会直接从API返回完整的结构化审计结果,可直接作为输出。如果
audit
返回200状态码,则跳过步骤5和6。
当未设置
UXUI_API_KEY
时,使用内部知识应用该框架,并在输出中注明此限制。

Framework Structure

框架结构

The 6-part taxonomy covers:
PartDomainKey Principles
Part 1Cognitive FoundationsCognitive Load (F.1.1.02), Miller's Law, Chunking, Hick's Law (F.2.2.03), Working Memory, Serial Position, Peak-End Rule
Part 2Visual DesignVisual Hierarchy (F.2.1.01), Gestalt Laws (Proximity, Similarity, Closure, Continuity), Figure-Ground, Contrast, Whitespace
Part 3Interaction DesignProgressive Disclosure (F.3.1.01), Fitts's Law (F.4.1.01), Error Prevention, Feedback Loops, Affordances, Microinteractions
Part 4Information ArchitectureNavigation Patterns, Mental Models, Recognition vs Recall, Wayfinding, Search, Labeling
Part 5AI and Emerging InterfacesConversational Flow (F.5.1.01), AI Transparency (F.5.2.01), Cognitive Load Calibration for AI, Automation Bias Prevention
Part 6Human-Centered DesignAccessibility, Inclusive Design, Trust Signals, Emotional Design, Ethical Patterns
Principle codes follow the format
F.[part].[chapter].[sequence]
. Example:
F.1.1.02
is Part 1, Chapter 1, Principle 02 (Cognitive Load).
6部分分类体系涵盖以下内容:
部分领域核心原则
第1部分认知基础Cognitive Load (F.1.1.02), Miller's Law, Chunking, Hick's Law (F.2.2.03), Working Memory, Serial Position, Peak-End Rule
第2部分视觉设计Visual Hierarchy (F.2.1.01), Gestalt Laws (Proximity, Similarity, Closure, Continuity), Figure-Ground, Contrast, Whitespace
第3部分交互设计Progressive Disclosure (F.3.1.01), Fitts's Law (F.4.1.01), Error Prevention, Feedback Loops, Affordances, Microinteractions
第4部分信息架构Navigation Patterns, Mental Models, Recognition vs Recall, Wayfinding, Search, Labeling
第5部分AI与新兴界面Conversational Flow (F.5.1.01), AI Transparency (F.5.2.01), Cognitive Load Calibration for AI, Automation Bias Prevention
第6部分以人为中心的设计Accessibility, Inclusive Design, Trust Signals, Emotional Design, Ethical Patterns
原则代码遵循
F.[部分].[章节].[序号]
格式。示例:
F.1.1.02
是第1部分、第1章、第02号原则(Cognitive Load)。

Evaluation Workflow

评估工作流程

Follow these steps in order. Do not skip steps.
请按以下顺序执行步骤,请勿跳过。

Step 1: Classify the Interface

步骤1:分类界面

Identify the interface type from the description. Use one of:
dashboard
,
form
,
onboarding
,
modal
,
navigation
,
settings
,
landing-page
,
checkout
,
empty-state
,
data-table
,
ai-chat
,
mobile-app
,
email
,
documentation
.
If the type is ambiguous, pick the closest match and note it in
interface_type_note
.
从描述中识别界面类型,可选类型包括:
dashboard
form
onboarding
modal
navigation
settings
landing-page
checkout
empty-state
data-table
ai-chat
mobile-app
email
documentation
如果类型不明确,请选择最接近的匹配项,并在
interface_type_note
中注明。

Step 2: Select Relevant Parts

步骤2:选择相关部分

Based on interface type, prioritize which framework parts to evaluate:
  • dashboard: Parts 1, 2, 4
  • form / checkout: Parts 1, 3, 4
  • onboarding: Parts 1, 3, 4, 6
  • navigation: Parts 1, 2, 4
  • ai-chat: Parts 1, 5, 6
  • modal: Parts 1, 3
  • landing-page: Parts 2, 3, 4, 6
Always evaluate Part 1 (Cognitive Foundations) for every interface type.
根据界面类型,优先选择需要评估的框架部分:
  • dashboard:第1、2、4部分
  • form / checkout:第1、3、4部分
  • onboarding:第1、3、4、6部分
  • navigation:第1、2、4部分
  • ai-chat:第1、5、6部分
  • modal:第1、3部分
  • landing-page:第2、3、4、6部分
所有界面类型都必须评估第1部分(认知基础)。

Step 3: Identify Violations

步骤3:识别违规情况

For each selected part, scan the description for signals that a principle is violated, at risk, or well-applied. Look for:
  • Information density signals (number of elements, options, steps)
  • Visual organization signals (hierarchy, grouping, whitespace)
  • Interaction signals (CTAs, affordances, feedback)
  • Trust and clarity signals (copy, error messages, empty states)
  • AI-specific signals (confidence displays, human override points)
针对每个选定部分,扫描描述以寻找原则被违反、存在风险或应用良好的信号。需关注:
  • 信息密度信号(元素、选项、步骤的数量)
  • 视觉组织信号(层级、分组、留白)
  • 交互信号(CTA、功能可见性、反馈)
  • 信任与清晰度信号(文案、错误提示、空状态)
  • AI特定信号(置信度显示、人工覆盖点)

Step 4: Enrich with Toolbox (if API key is set)

步骤4:通过工具集增强内容(若已设置API密钥)

Preferred path: Call
audit
with
{"description": "<interface description>"}
. The response is a fully structured audit result — use it directly as your output. Skip Steps 5 and 6 if
audit
returns a 200.
Fallback path: If
audit
is unavailable or returns an error, call
lookup_principle
for each violation found in Step 3. Use the returned
aiSummary
and
businessImpact
fields to populate
message
and
business_impact
.
If all tool calls fail or return non-200, continue without enrichment. Set
api_enriched: false
.
Slugs for common principles:
  • cognitive-load
    ,
    hicks-law
    ,
    millers-law
    ,
    chunking
    ,
    working-memory
  • progressive-disclosure
    ,
    fitts-law
    ,
    serial-position-effect
  • visual-hierarchy
    ,
    law-of-proximity
    ,
    figure-ground
  • recognition-rather-than-recall
    ,
    mental-model
  • cognitive-load-calibration-ai
    ,
    automation-bias-prevention
优先路径:调用
audit
工具,传入参数
{"description": "<界面描述>"}
。返回的响应是完整的结构化审计结果——直接将其作为输出即可。如果
audit
返回200状态码,跳过步骤5和6。
备选路径:如果
audit
不可用或返回错误,为步骤3中发现的每一项违规调用
lookup_principle
工具。使用返回的
aiSummary
businessImpact
字段填充
message
business_impact
如果所有工具调用失败或返回非200状态码,继续不使用增强内容,设置
api_enriched: false
常见原则的Slug:
  • cognitive-load
    ,
    hicks-law
    ,
    millers-law
    ,
    chunking
    ,
    working-memory
  • progressive-disclosure
    ,
    fitts-law
    ,
    serial-position-effect
  • visual-hierarchy
    ,
    law-of-proximity
    ,
    figure-ground
  • recognition-rather-than-recall
    ,
    mental-model
  • cognitive-load-calibration-ai
    ,
    automation-bias-prevention

Step 5: Score and Band

步骤5:评分与分级

Score from 0 to 100. Start at 100 and deduct:
  • critical
    finding: -15 points
  • warning
    finding: -7 points
  • suggestion
    finding: -3 points
Band thresholds:
  • 85-100:
    excellent
  • 65-84:
    good
  • 40-64:
    fair
  • 0-39:
    poor
Cap deductions at 0 (score cannot go below 0).
评分范围为0到100分,初始分为100分,根据以下规则扣分:
  • critical
    (严重)问题:扣15分
  • warning
    (警告)问题:扣7分
  • suggestion
    (建议)问题:扣3分
分级阈值:
  • 85-100分:
    excellent
    (优秀)
  • 65-84分:
    good
    (良好)
  • 40-64分:
    fair
    (一般)
  • 0-39分:
    poor
    (较差)
扣分后最低分为0分(分数不能低于0)。

Step 6: Output JSON

步骤6:输出JSON

Return exactly this structure. No prose before or after the JSON block.
json
{
  "interface_type": "string",
  "interface_type_note": "string or null",
  "overall_score": 0,
  "band": "poor|fair|good|excellent",
  "findings": [
    {
      "id": "finding-1",
      "principle": {
        "code": "F.1.1.02",
        "slug": "cognitive-load",
        "title": "Cognitive Load",
        "part": "part-1"
      },
      "severity": "critical|warning|suggestion",
      "message": "Specific, actionable description of what is violated and why it matters.",
      "remediation": "Concrete fix with measurable outcome.",
      "business_impact": "String from principle data, or null if not enriched."
    }
  ],
  "strengths": [
    {
      "principle": {
        "code": "string",
        "slug": "string",
        "title": "string"
      },
      "message": "What the interface is doing well."
    }
  ],
  "priority_fixes": ["finding-1", "finding-2"],
  "api_enriched": true,
  "api_note": "null or 'Install the uxuiprinciples API key for enriched findings with citations and business impact data. See uxuiprinciples.com/pricing'"
}
priority_fixes
lists finding IDs in recommended fix order: critical first, then warnings that most affect the primary user action.
严格返回以下结构,JSON块前后不得添加任何散文式内容。
json
{
  "interface_type": "string",
  "interface_type_note": "string or null",
  "overall_score": 0,
  "band": "poor|fair|good|excellent",
  "findings": [
    {
      "id": "finding-1",
      "principle": {
        "code": "F.1.1.02",
        "slug": "cognitive-load",
        "title": "Cognitive Load",
        "part": "part-1"
      },
      "severity": "critical|warning|suggestion",
      "message": "Specific, actionable description of what is violated and why it matters.",
      "remediation": "Concrete fix with measurable outcome.",
      "business_impact": "String from principle data, or null if not enriched."
    }
  ],
  "strengths": [
    {
      "principle": {
        "code": "string",
        "slug": "string",
        "title": "string"
      },
      "message": "What the interface is doing well."
    }
  ],
  "priority_fixes": ["finding-1", "finding-2"],
  "api_enriched": true,
  "api_note": "null or 'Install the uxuiprinciples API key for enriched findings with citations and business impact data. See uxuiprinciples.com/pricing'"
}
priority_fixes
按推荐修复顺序列出问题ID:先严重问题,再是对主要用户操作影响最大的警告问题。

Severity Guidelines

严重程度指南

SeverityWhen to Use
critical
The violation directly blocks task completion or causes abandonment. Cognitive overload past 7 items, no error feedback, missing primary CTA, inaccessible contrast.
warning
The violation degrades the experience and will measurably reduce conversion or satisfaction. Suboptimal choice count, unclear hierarchy, missing affordances.
suggestion
An improvement opportunity. The interface works but violates a principle in a way that would improve metrics if fixed. Microcopy, spacing, progressive disclosure opportunities.
严重程度使用场景
critical
违规直接阻碍任务完成或导致用户放弃。例如:认知过载超过7个元素、无错误反馈、缺少主CTA、对比度不符合无障碍要求。
warning
违规降低体验质量,会显著降低转化率或用户满意度。例如:选项数量不理想、层级不清晰、缺少功能可见性。
suggestion
可优化的机会。界面可正常使用,但违反原则的情况若修复可提升指标。例如:微文案、间距、渐进式披露的优化空间。

Edge Cases

边缘情况

Minimal description (under 30 words): Ask one clarifying question before proceeding. "What is the primary action a user should complete on this screen?" Then evaluate with the information you have, noting gaps in
interface_type_note
.
No violations found: Return at least 2 strengths. Set
findings: []
. Score 100, band
excellent
. This is valid output.
Multiple interface types in one description (e.g., dashboard + settings sidebar): Identify the dominant interface type. Add a note in
interface_type_note
. Evaluate the dominant type.
AI interface without AI-specific signals: Skip Part 5 evaluation. Do not fabricate AI-related findings.
Vague copy like "users can see their data": Do not hallucinate specifics. Evaluate what you can observe from the description. Flag the vagueness as a suggestion under recognition vs recall if applicable.
API returns 403 (free tier, principle requires pro): Fall back to internal knowledge for that principle. Note in
api_enriched: false
.
描述过于简短(不足30词):先提出一个澄清问题再继续。例如:"用户在该页面需要完成的主要操作是什么?"然后根据已有信息进行评估,并在
interface_type_note
中注明信息缺口。
未发现违规情况:返回至少2项优势,设置
findings: []
。评分为100分,等级为
excellent
。这是有效的输出。
描述中包含多种界面类型(如:dashboard + 设置侧边栏):识别主导界面类型,在
interface_type_note
中添加说明,针对主导类型进行评估。
AI界面无AI特定信号:跳过第5部分的评估,不得编造AI相关问题。
模糊描述如"用户可查看其数据":不得虚构细节,仅根据描述中可观察到的内容进行评估。若适用,将模糊性标记为Recognition vs Recall原则下的建议。
API返回403状态码(免费版,原则需专业版权限):针对该原则使用内部知识进行评估,在
api_enriched: false
中注明。

Examples

示例

Example 1: Dashboard with Overload Issues

示例1:存在过载问题的仪表盘

Input:
Admin dashboard with 15 KPI cards, 4 filter dropdowns, a data table showing 50 rows, 3 chart widgets, and a sidebar navigation with 12 items.
Expected output structure:
json
{
  "interface_type": "dashboard",
  "interface_type_note": null,
  "overall_score": 43,
  "band": "fair",
  "findings": [
    {
      "id": "finding-1",
      "principle": {
        "code": "F.1.1.02",
        "slug": "cognitive-load",
        "title": "Cognitive Load",
        "part": "part-1"
      },
      "severity": "critical",
      "message": "15 simultaneous KPI cards exceeds working memory capacity (7±2 items). Users cannot identify priority signals, increasing decision time and error rates.",
      "remediation": "Group KPIs into 3-5 thematic sections. Surface the 5 most critical metrics above the fold. Move secondary metrics to an expandable section or secondary view.",
      "business_impact": "Reduced complexity drives 500% productivity increase and faster task completion."
    },
    {
      "id": "finding-2",
      "principle": {
        "code": "F.2.2.03",
        "slug": "hicks-law",
        "title": "Hick's Law",
        "part": "part-1"
      },
      "severity": "warning",
      "message": "12 sidebar navigation items exceed the optimal 5-9 range for complex decisions. Each extra item adds ~150ms decision time per visit.",
      "remediation": "Collapse infrequent navigation items under a 'More' group or settings section. Keep primary navigation to 5-7 items.",
      "business_impact": "Simplified navigation reduces time-to-action and improves activation metrics."
    }
  ],
  "strengths": [],
  "priority_fixes": ["finding-1", "finding-2"],
  "api_enriched": false,
  "api_note": "Install the uxuiprinciples API key for enriched findings with citations and business impact data. See uxuiprinciples.com/pricing"
}
输入:
Admin dashboard with 15 KPI cards, 4 filter dropdowns, a data table showing 50 rows, 3 chart widgets, and a sidebar navigation with 12 items.
预期输出结构:
json
{
  "interface_type": "dashboard",
  "interface_type_note": null,
  "overall_score": 43,
  "band": "fair",
  "findings": [
    {
      "id": "finding-1",
      "principle": {
        "code": "F.1.1.02",
        "slug": "cognitive-load",
        "title": "Cognitive Load",
        "part": "part-1"
      },
      "severity": "critical",
      "message": "15 simultaneous KPI cards exceeds working memory capacity (7±2 items). Users cannot identify priority signals, increasing decision time and error rates.",
      "remediation": "Group KPIs into 3-5 thematic sections. Surface the 5 most critical metrics above the fold. Move secondary metrics to an expandable section or secondary view.",
      "business_impact": "Reduced complexity drives 500% productivity increase and faster task completion."
    },
    {
      "id": "finding-2",
      "principle": {
        "code": "F.2.2.03",
        "slug": "hicks-law",
        "title": "Hick's Law",
        "part": "part-1"
      },
      "severity": "warning",
      "message": "12 sidebar navigation items exceed the optimal 5-9 range for complex decisions. Each extra item adds ~150ms decision time per visit.",
      "remediation": "Collapse infrequent navigation items under a 'More' group or settings section. Keep primary navigation to 5-7 items.",
      "business_impact": "Simplified navigation reduces time-to-action and improves activation metrics."
    }
  ],
  "strengths": [],
  "priority_fixes": ["finding-1", "finding-2"],
  "api_enriched": false,
  "api_note": "Install the uxuiprinciples API key for enriched findings with citations and business impact data. See uxuiprinciples.com/pricing"
}

Example 2: Minimal Input

示例2:极简输入

Input:
Login page.
Expected behavior: Ask one clarifying question. "What elements does the login page contain? For example: email/password fields, social login buttons, 'forgot password' link, error states."
输入:
Login page.
预期行为: 提出一个澄清问题。例如:"登录页面包含哪些元素?比如:邮箱/密码字段、社交登录按钮、'忘记密码'链接、错误状态。"

Completion Criteria

完成标准

The skill output is complete when:
  1. interface_type
    is set to one of the allowed values
  2. Every finding has a
    principle.code
    in
    F.X.X.XX
    format
  3. Every finding has a non-empty
    message
    and
    remediation
  4. severity
    is one of:
    critical
    ,
    warning
    ,
    suggestion
  5. overall_score
    is between 0 and 100
  6. band
    matches the score threshold
  7. priority_fixes
    lists only IDs that exist in
    findings
  8. api_enriched
    accurately reflects whether toolbox calls succeeded
  9. The output is valid JSON with no prose before or after
当满足以下条件时,技能输出视为完成:
  1. interface_type
    设置为允许的值之一
  2. 每个问题的
    principle.code
    符合
    F.X.X.XX
    格式
  3. 每个问题的
    message
    remediation
    均不为空
  4. severity
    为以下值之一:
    critical
    warning
    suggestion
  5. overall_score
    在0到100之间
  6. band
    与评分阈值匹配
  7. priority_fixes
    仅包含
    findings
    中存在的ID
  8. api_enriched
    准确反映工具集调用是否成功
  9. 输出为有效的JSON,前后无散文式内容