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Agent Skill · 研究检索

nng-ux-heuristics(NNG 用户体验启发法)

用于辅助界面设计、视觉规范、排版、配色、布局和交互体验优化。它适合让 Agent 根据产品场景整理页面结构、生成 UI 方案、检查视觉一致性或改进组件层级。使用时需要结合现有品牌、设计系统和用户任务,不应只堆装饰元素;涉及真实页面改动时,应通过截图或浏览器预览检查文本溢出、对齐和响应式表现。

nng-ux-heuristics 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为需要联网;许可证信息还不明确,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 13,370。

总安装 9,442周安装 255GitHub Stars 3下载 1,630核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:nng-ux-heuristics(NNG 用户体验启发法)
来源仓库:https://github.com/phazurlabs/ux-ui-mastery
仓库路径:skills/nng-ux-heuristics
安装命令:
npx skills add https://github.com/phazurlabs/ux-ui-mastery --skill 'NNG UX Heuristics'
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/phazurlabs/ux-ui-mastery --skill 'NNG UX Heuristics'

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

用于辅助界面设计和交互体验优化。适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。适合整理页面结构、生成 UI 方案或检查视觉一致性。结合现有品牌和设计系统使用,避免孤立生成片段。涉及真实页面改动时需通过截图或浏览器预览验证效果。

nng-ux-heuristics 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

来源仓库内路径:skills/nng-ux-heuristics

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/phazurlabs/ux-ui-mastery --skill 'NNG UX Heuri…;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要需要联网,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

nng-ux-heuristics 怎么安装?

在终端执行 npx skills add https://github.com/phazurlabs/ux-ui-mastery --skill 'NNG UX Heuristics'。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

nng-ux-heuristics 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

nng-ux-heuristics 需要什么权限?

权限级别是需要联网。该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

nng-ux-heuristics 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

nng-ux-heuristics 用的人多吗?

公开数据是累计安装 9,442 次,近一周安装 255 次,下载 1,630 次,GitHub 3 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

nng-ux-heuristics 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
nng-ux-heuristics

NNG 用户体验启发法 · 本页

9,4423需要联网未明确通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

NNG UX Heuristics — Modern Evaluation Framework

Foundation

Jakob Nielsen's 10 usability heuristics remain the most validated and widely-used framework for evaluating interface quality. Originally published in 1994 and continuously refined by Nielsen Norman Group, these heuristics apply universally across platforms, devices, and interaction paradigms — from traditional GUIs to AI-native and spatial interfaces.

The Core Philosophy (Don Norman + Jakob Nielsen)

Usability is not optional decoration — it is the fundamental determinant of whether a product succeeds. Every interface element must earn its place by serving user goals. The system exists to serve the user, never the reverse.

The 10 Heuristics — Modern Interpretation

H1: Visibility of System Status

The system must always keep users informed about what is going on through appropriate feedback within reasonable time.

Modern application:

  • Show loading states with progress indicators, not spinners alone — communicate *what* is happening
  • AI systems must indicate when they are processing, uncertain, or complete
  • Real-time collaboration needs presence indicators and change attribution
  • Background processes require persistent but non-intrusive status communication
  • Skeleton screens communicate structure before content arrives

Severity when violated: High — users who cannot determine system state abandon tasks at 3x the normal rate.

H2: Match Between System and Real World

The system must speak the users' language, with words, phrases, and concepts familiar to the user rather than system-oriented terms. Follow real-world conventions, making information appear in a natural and logical order.

Modern application:

  • Use domain-specific language appropriate to the audience — medical apps use clinical terms for clinicians, plain language for patients
  • AI confidence should be expressed in human-understandable terms, not raw probabilities
  • Icon metaphors must evolve — the floppy disk "save" icon persists but new domains need fresh metaphors
  • Voice interfaces must match conversational expectations and cultural norms
  • Spatial interfaces must respect physical-world affordances (gravity, proximity, occlusion)

Severity when violated: Medium-High — vocabulary mismatch causes 40%+ error rates in form completion.

H3: User Control and Freedom

Users often perform actions by mistake. The system must provide a clearly marked "emergency exit" to leave an unwanted state without going through an extended process. Support undo and redo.

Modern application:

  • Every destructive action requires confirmation with clear consequences stated
  • Multi-level undo (not just single-step) is the baseline expectation
  • AI-generated content must be editable, rejectable, and regenerable
  • Autosave with version history replaces manual save paradigms
  • Gesture-based interfaces need clear gesture cancellation paths

Severity when violated: Critical — lack of undo is the #1 source of user anxiety and data loss complaints.

H4: Consistency and Standards

Users should not have to wonder whether different words, situations, or actions mean the same thing. Follow platform conventions.

Modern application:

  • Follow platform-specific patterns: iOS Human Interface Guidelines, Material Design 3, Fluent Design
  • Internal consistency across product suite matters as much as platform consistency
  • Design tokens enforce consistency programmatically — do not rely on manual enforcement
  • AI behavior consistency: same prompt patterns should produce predictably similar interaction styles
  • Cross-device consistency: the experience must feel unified across mobile, desktop, and wearable

Severity when violated: Medium — inconsistency increases learning time by 25-50% and erodes trust.

H5: Error Prevention

Even better than good error messages is a careful design which prevents a problem from occurring in the first place. Either eliminate error-prone conditions or check for them and present users with a confirmation option before they commit to the action.

Modern application:

  • Inline validation as users type, not on submission
  • Smart defaults reduce decision fatigue and error opportunity
  • Constrained inputs (date pickers, dropdowns) prevent format errors
  • AI should flag potential issues before users commit (smart warnings)
  • Dangerous zones in interfaces should have increased friction (confirmation dialogs, delay timers)

Severity when violated: High — prevention is 10x cheaper than recovery.

H6: Recognition Rather Than Recall

Minimize the user's memory load by making elements, actions, and options visible. The user should not have to remember information from one part of the interface to another. Information required to use the design should be visible or easily retrievable.

Modern application:

  • Recent items, favorites, and contextual suggestions reduce memory burden
  • Command palettes (Cmd+K pattern) combine recognition with speed
  • AI-powered suggestions surface relevant actions based on context
  • Breadcrumbs, progress indicators, and contextual help maintain orientation
  • Auto-complete and type-ahead search leverage recognition over recall

Severity when violated: Medium — excessive recall demands cause 60% task abandonment in complex workflows.

H7: Flexibility and Efficiency of Use

Accelerators — unseen by the novice user — may speed up the interaction for the expert user such that the system can cater to both inexperienced and experienced users. Allow users to tailor frequent actions.

Modern application:

  • Keyboard shortcuts with discoverable overlay (hold modifier key to reveal)
  • Customizable toolbars and workflows for power users
  • Progressive disclosure: simple by default, powerful on demand
  • AI adapts to user skill level over time — suggesting shortcuts to frequent users
  • Batch operations and bulk editing for data-heavy workflows

Severity when violated: Low-Medium for basic use, High for professional/enterprise tools.

H8: Aesthetic and Minimalist Design

Dialogues should not contain information which is irrelevant or rarely needed. Every extra unit of information in a dialogue competes with the relevant units of information and diminishes their relative visibility.

Modern application (Dieter Rams: "Less, but better"):

  • Content-to-chrome ratio should favor content — minimize interface overhead
  • Progressive disclosure over cluttered screens
  • White space is a design element, not wasted space
  • Information density must match user expertise — dashboards for analysts, simplified views for casual users
  • AI interfaces should show results first, process second

Severity when violated: Medium — cluttered interfaces reduce task completion by 20% and user satisfaction by 40%.

H9: Help Users Recognize, Diagnose, and Recover from Errors

Error messages should be expressed in plain language (no codes), precisely indicate the problem, and constructively suggest a solution.

Modern application:

  • Error messages must state: what happened, why it happened, and exactly how to fix it
  • Inline errors positioned near the source, not in distant toast notifications
  • AI failures should explain limitations honestly and suggest alternatives
  • Network errors should offer retry with offline capability where possible
  • Form validation errors must persist until resolved and disappear immediately once fixed

Severity when violated: High — poor error recovery doubles support ticket volume.

H10: Help and Documentation

Even though it is better if the system can be used without documentation, it may be necessary to provide help and documentation. Any such information should be easy to search, focused on the user's task, list concrete steps, and not be too large.

Modern application:

  • Contextual help tooltips and inline guidance over separate documentation portals
  • Onboarding flows that teach by doing, not by reading
  • AI-powered help that answers natural language questions about the interface
  • Empty states as teaching moments — guide first-time users to valuable actions
  • Searchable, task-oriented help organized by user goals, not feature names

Severity when violated: Low for simple apps, High for complex professional tools.

Heuristic Evaluation Methodology

Preparation Phase

  1. Define the scope: which flows, screens, or components to evaluate
  2. Select 3-5 evaluators with diverse expertise (NNG recommends 3-5 for optimal cost-benefit)
  3. Prepare user personas and key task scenarios
  4. Set severity rating scale (0-4, defined below)

Evaluation Phase

  1. Each evaluator independently reviews the interface against all 10 heuristics
  2. Walk through each task scenario noting violations
  3. Rate each violation by severity (see scale)
  4. Capture screenshots or recordings of each issue
  5. Note which heuristic(s) each violation maps to

Severity Rating Scale

  • 0 — Not a usability problem: Cosmetic only, no user impact
  • 1 — Cosmetic problem: Fix when convenient, low priority
  • 2 — Minor usability problem: Causes slight delays, fix with moderate priority
  • 3 — Major usability problem: Causes significant difficulty, fix with high priority
  • 4 — Usability catastrophe: Prevents task completion, must fix before release

Reporting Phase

  1. Consolidate findings across evaluators
  2. Deduplicate and merge related issues
  3. Prioritize by severity × frequency × user impact
  4. Generate actionable recommendations with specific implementation guidance
  5. Track remediation through design and development

Cross-Referencing

  • For visual design evaluation criteria, reference ui-visual-design-system
  • For accessibility-specific evaluation, reference accessibility-inclusive-design
  • For mobile-specific heuristic application, reference mobile-ux-design
  • For AI interface evaluation, reference ai-spatial-voice-ux

v3.0 Cross-References

The v3.0 upgrade introduces skills that deepen and extend heuristic evaluation into scientific foundations, structured critique, and production implementation.

Cognitive Psychology Foundations — cognitive-psychology-ux

Each heuristic maps to underlying cognitive science. The cognitive-psychology-ux skill provides the scientific research behind why these heuristics work:

  • H6 Recognition Rather Than Recall connects directly to the distinction between recognition memory and recall memory. The cognitive psychology skill covers working memory capacity (Miller's 7 plus/minus 2, Cowan's refined 4 plus/minus 1), encoding specificity, and context-dependent retrieval — explaining *why* recognition is cognitively cheaper than recall.
  • H8 Aesthetic and Minimalist Design maps to cognitive load theory (Sweller). The skill details intrinsic, extraneous, and germane cognitive load, providing the scientific basis for why every extraneous element degrades performance.
  • H5 Error Prevention relates to mental model theory (Johnson-Laird). The skill covers how users form mental models, the gulf of execution and evaluation (Norman), and how design can align system behavior with user expectations to prevent errors at the cognitive level.

Structured Design Reviews — design-critique-case-studies

The design-critique-case-studies skill provides structured frameworks for applying heuristic evaluations in team settings — including critique session facilitation, severity calibration across evaluators, and case study examples of heuristic violations in real-world products with documented remediation outcomes.

Production Implementation — component-patterns-code

The component-patterns-code skill contains production-ready React and SwiftUI component patterns that demonstrate heuristic compliance in code — including loading state patterns (H1), undo/redo implementations (H3), inline validation (H5), and command palette implementations (H6, H7). Use these as reference implementations when translating heuristic evaluation findings into development tickets.

Key Sources

  • Nielsen, J. (1994). "10 Usability Heuristics for User Interface Design" — updated 2024
  • Norman, D. (2013). "The Design of Everyday Things" — revised edition
  • NNG Group research articles and studies (2020-2025)
  • Rams, D. "Ten Principles for Good Design"

平台分布

Codex

35.98%
按下载量换算586

Claude

28.9%
按下载量换算471

Cursor

16.83%
按下载量换算274

Gemini CLI

8.57%
按下载量换算140

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。目前只有一个公开来源,建议同时核对源仓库。

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