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Agent Skill · 前端设计

diagnostics(diagnostics 搜索)

diagnostics 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要围绕仓库状态、代码变更或协作事项进行整理时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

diagnostics 是前端设计类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为调用外部服务;许可证信息还不明确,第三方扫描已通过,按安装量在前端设计类的 10,216 个 Skill 里排第 8,889。

总安装 250周安装 10GitHub Stars 公开资料未说明下载 81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:diagnostics(diagnostics 搜索)
来源仓库:https://github.com/personizeai/personize-skills
仓库路径:skills/diagnostics
安装命令:
npx skills add https://github.com/personizeai/personize-skills --skill diagnostics
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/personizeai/personize-skills --skill diagnostics

这个 Skill 是做什么的

前端设计类 Skill 关注页面结构、视觉规范和组件写法,输出通常是可运行的界面代码。

用于处理 GitHub 仓库、Issue、Pull Request 等协作信息。适合围绕代码变更、仓库状态进行整理和分析。通过 GitHub 安装,支持主流 AI 编程工具集成。使用前需确认权限范围和仓库维护状态。diagnostics 属于前端设计类 Skill,可作为该场景下的辅助能力补充。

建议结合原始 README 核验具体用法,避免触发不必要的命令执行。

来源仓库内路径:skills/diagnostics

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/personizeai/personize-skills --skill diagnosti…;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

    它需要调用外部服务,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

diagnostics 怎么安装?

在终端执行 npx skills add https://github.com/personizeai/personize-skills --skill diagnostics。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

diagnostics 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。

diagnostics 需要什么权限?

权限级别是调用外部服务。该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

diagnostics 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。

diagnostics 用的人多吗?

公开数据是累计安装 250 次,近一周安装 10 次,下载 81 次。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。

diagnostics 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。
  • 需要处理前端设计类任务、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。

前端设计类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
frontend-design

前端设计 · Codex、Claude

8,823,360126,072只读MIT通过
vercel-composition-patterns

Vercel 组合模式 · Codex、Claude

3,858,81625,893需要联网MIT通过
vercel-react-native-skills

Vercel React native skills 前端 · Codex、Claude

2,468,66425,878只读MIT通过
adapt

adapt 搜索 · Codex、Claude

2,027,04023,125操作浏览器未明确通过
bolder

bolder 分析 · Codex、Claude

2,004,28823,130只读未明确通过
diagnostics

diagnostics 搜索 · 本页

250—调用外部服务未明确通过

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

Skill: Diagnostics

Verify setup and troubleshoot the Personize stack. Two modes:

  • VERIFY — Proactive. Run after setting up memory, governance, pipelines, or workspaces to confirm they work.
  • FIX — Reactive. Jump to the action that matches the symptom when something breaks.

When to Use This Skill

Verify mode:

  • Just finished memorizing data and want to confirm it's stored and recallable
  • Just set up guidelines and want to confirm agents can see them
  • Just wired a pipeline and want to run one record end-to-end
  • Just set up a shared workspace and want to confirm agents can read/write
  • Want to run a periodic health check

Fix mode:

  • Recall returns irrelevant, empty, or noisy results
  • Memorized data isn't being extracted correctly
  • Guidelines aren't reaching agents or return wrong content
  • Getting 429 rate limit errors or partial batch syncs
  • Trigger.dev or n8n workflows are failing
  • Shared workspace is going stale or agents aren't contributing

When NOT to Use This Skill

  • Need to store data → use entity-memory
  • Need to create guidelines → use governance
  • Need to build a pipeline → use code-pipelines or no-code-pipelines
  • Need to understand the architecture → use solution-architect

Works With Both SDK and MCP

InterfaceHow it worksBest for
SDK (@personize/sdk)Run verification scripts locallyDevelopers, CI/CD
MCP (Model Context Protocol)Use memory_recall_pro, ai_smart_guidelines tools interactivelyClaude Desktop, ChatGPT, Cursor

Quick Smoke Test

If the developer isn't sure what's wrong or just wants to verify everything works, run this:

import { Personize } from '@personize/sdk';
const client = new Personize({ secretKey: process.env.PERSONIZE_SECRET_KEY! });

// 1. Auth — can we connect?
try {
  const me = await client.me();
  console.log(`✅ Auth: ${me.data.organization.name} (${me.data.plan.name})`);
} catch (e) {
  console.log('❌ Auth failed:', e.message);
  console.log('   → Check PERSONIZE_SECRET_KEY');
}

// 2. Memory — can we store and retrieve?
try {
  await client.memory.memorize({
    email: 'diagnostics-test@example.com',
    content: 'Test record for diagnostics. This person works at Acme Corp as a VP of Engineering.',
    enhanced: true,
  });
  const recall = await client.memory.recall({
    query: 'Who works at Acme Corp?',
    email: 'diagnostics-test@example.com',
  });
  console.log(`✅ Memory: ${recall.data.memories.length > 0 ? 'stored and recallable' : '⚠️ stored but not yet recallable (indexing may take 1-2 min)'}`);
} catch (e) {
  console.log('❌ Memory failed:', e.message);
  if (e.message.includes('429')) console.log('   → Rate limited. See FIX: RATE-LIMITS.');
}

// 3. Governance — can we fetch guidelines?
try {
  const guidelines = await client.ai.smartGuidelines({ message: 'test verification' });
  console.log(`✅ Governance: ${guidelines.data.compiledContext ? 'responding' : '⚠️ no guidelines set up yet'}`);
} catch (e) {
  console.log('❌ Guidelines failed:', e.message);
}

// 4. Digest — can we compile context?
try {
  const digest = await client.memory.smartDigest({
    email: 'diagnostics-test@example.com',
    include_properties: true,
    include_memories: true,
  });
  console.log(`✅ Digest: ${digest.data.compiledContext ? 'compiling context' : '⚠️ empty'}`);
} catch (e) {
  console.log('❌ Digest failed:', e.message);
}

MCP equivalent

1. Call memory_store_pro with content "Test record. Works at Acme Corp as VP Engineering." and email "diagnostics-test@example.com"
2. Call memory_recall_pro with query "Who works at Acme Corp?" and email "diagnostics-test@example.com"
3. Call ai_smart_guidelines with message "test verification"
4. Confirm each returns data

Based on results, jump to the appropriate VERIFY or FIX action below.


VERIFY Actions

Use after setting up a capability to prove it works.

ActionWhen to UseReference
VERIFY-MEMORYAfter memorizing data — confirm it's stored and recallablereference/verify-memory.md
VERIFY-GOVERNANCEAfter setting up guidelines — confirm agents can see themreference/verify-governance.md
VERIFY-PIPELINEAfter wiring a pipeline — run one record end-to-endreference/verify-pipeline.md
VERIFY-WORKSPACEAfter setting up a shared workspace — confirm agents can read/writereference/verify-workspace.md
HEALTH-CHECKOngoing — diagnose quality, performance, and coverage issuesreference/health-check.md

FIX Actions

Use when something is broken. Jump to the action that matches the symptom.

ActionWhen to UseReference
BAD-RECALLRecall returns irrelevant, empty, or noisy resultsreference/bad-recall.md
BAD-EXTRACTIONMemorized data isn't being extracted correctlyreference/bad-extraction.md
GOVERNANCE-MISSGuidelines aren't reaching agents or return wrong contentreference/governance-miss.md
RATE-LIMITSGetting 429 errors or partial batch syncsreference/rate-limits.md
PIPELINE-FAILURETrigger.dev/n8n workflows failing or producing bad outputreference/pipeline-failure.md
WORKSPACE-STALEAgents not contributing or workspace going stalereference/workspace-stale.md

Constraints

Keywords follow RFC 2119: MUST = non-negotiable, SHOULD = strong default (override with stated reasoning), MAY = agent discretion.
  1. MUST run the smoke test or appropriate verify action after every setup — because untested setups create false confidence and delayed failures.
  2. MUST run diagnostic steps before suggesting fixes — because guessing wastes time and can introduce new problems.
  3. MUST use real queries that match the developer's actual use case, not generic test strings — because verification with irrelevant queries can pass while real queries fail.
  4. SHOULD show the developer the actual API response, not just pass/fail — because seeing the data builds understanding and catches quality issues.
  5. SHOULD rank root causes by likelihood and check the most likely first — because systematic diagnosis is faster than shotgun debugging.
  6. SHOULD verify the fix worked by re-running the failing operation — because a fix that doesn't resolve the symptom isn't a fix.
  7. SHOULD clean up test data after verification — because leftover test records pollute memory and confuse downstream agents.

平台分布

Codex

36.01%
按下载量换算29

Claude

29.45%
按下载量换算24

Cursor

18.23%
按下载量换算15

Gemini CLI

9.29%
按下载量换算8

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

调用外部服务

该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

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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