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diagnosticsdiagnostics 搜索

Agent Skill

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。

总安装

250

周安装

10

GitHub Stars

公开资料未说明

下载量

81
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

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

简介

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。

SKILL.md

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.

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

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

external-service

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。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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