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add-ai-integration添加 AI 集成

Agent Skill

add-ai-integration 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

194

周安装

8

GitHub Stars

8,569

下载量

63
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:add-ai-integration(添加 AI 集成)
来源仓库:https://github.com/getsentry/sentry-javascript
仓库路径:skills/add-ai-integration
安装命令:
npx skills add https://github.com/getsentry/sentry-javascript --skill add-ai-integration
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/getsentry/sentry-javascript --skill add-ai-integration

简介

add-ai-integration 提供 Sentry JavaScript SDK 中 AI 集成的标准化实现模式与代码组织规范。

  • 涵盖 OpenTelemetry 支持、回调钩子、客户端包装等多种集成方式的选择指导。
  • 适用于 Node.js、浏览器或云函数等多运行时环境下的 AI SDK 埋点与监控接入。
  • 安装命令为 npx skills add https://github.com/getsentry/sentry-javascript --skill add-ai-integration。
  • 实现时需根据运行时环境选择正确目录存放集成代码,禁止放入 packages/core/。

SKILL.md

Adding a New AI Integration

Decision Tree

Does the AI SDK have native OpenTelemetry support?
|- YES -> Does it emit OTel spans automatically?
|   |- YES (like Vercel AI) -> Pattern 1: OTel Span Processors
|   +- NO -> Pattern 2: OTel Instrumentation (wrap client)
+- NO -> Does the SDK provide hooks/callbacks?
    |- YES (like LangChain) -> Pattern 3: Callback/Hook Based
    +- NO -> Pattern 4: Client Wrapping

Runtime-Specific Placement

If an AI SDK only works in one runtime, code lives exclusively in that runtime's package. Do NOT add it to packages/core/.

  • Node.js-only -> packages/node/src/integrations/tracing/{provider}/
  • Cloudflare-only -> packages/cloudflare/src/integrations/tracing/{provider}.ts
  • Browser-only -> packages/browser/src/integrations/tracing/{provider}/
  • Multi-runtime -> shared core in packages/core/src/tracing/{provider}/ with runtime-specific wrappers

Span Hierarchy

  • gen_ai.invoke_agent — parent/pipeline spans (chains, agents, orchestration)
  • gen_ai.chat, gen_ai.generate_text, etc. — child spans (actual LLM calls)

Shared Utilities (packages/core/src/tracing/ai/)

  • gen-ai-attributes.ts — OTel Semantic Convention attribute constants. Always use these, never hardcode.
  • utils.tssetTokenUsageAttributes(), getTruncatedJsonString(), truncateGenAiMessages(), buildMethodPath()
  • Only use attributes from Sentry Gen AI Conventions.

Streaming

  • Non-streaming: startSpan(), set attributes from response
  • Streaming: startSpanManual(), accumulate state via async generator or event listeners, set GEN_AI_RESPONSE_STREAMING_ATTRIBUTE: true, call span.end() in finally block
  • Detect via params.stream === true
  • References: openai/streaming.ts (async generator), anthropic-ai/streaming.ts (event listeners)

Token Accumulation

  • Child spans: Set tokens directly from API response via setTokenUsageAttributes()
  • Parent spans (invoke_agent): Accumulate from children using event processor (see vercel-ai/)

Pattern 1: OTel Span Processors

Use when: SDK emits OTel spans automatically (Vercel AI)

  1. Core: Create add{Provider}Processors() in packages/core/src/tracing/{provider}/index.ts — registers spanStart listener + event processor
  2. Node.js: Add callWhenPatched() optimization in packages/node/src/integrations/tracing/{provider}/index.ts — defers registration until package is imported
  3. Edge: Direct registration in packages/cloudflare/src/integrations/tracing/{provider}.ts — no OTel, call processors immediately

Reference: packages/node/src/integrations/tracing/vercelai/

Pattern 2: OTel Instrumentation (Client Wrapping)

Use when: SDK has no native OTel support (OpenAI, Anthropic, Google GenAI)

  1. Core: Create instrument{Provider}Client() in packages/core/src/tracing/{provider}/index.ts — Proxy to wrap client methods, create spans manually
  2. Node.js instrumentation.ts: Patch module exports, wrap client constructor. Check _INTERNAL_shouldSkipAiProviderWrapping() for LangChain compatibility.
  3. Node.js index.ts: Export integration function using generateInstrumentOnce() helper

Reference: packages/node/src/integrations/tracing/openai/

Pattern 3: Callback/Hook Based

Use when: SDK provides lifecycle hooks (LangChain, LangGraph)

  1. Core: Create create{Provider}CallbackHandler() — implement SDK's callback interface, create spans in callbacks
  2. Node.js instrumentation.ts: Auto-inject callbacks by patching runnable methods. Disable underlying AI provider wrapping.

Reference: packages/node/src/integrations/tracing/langchain/

Auto-Instrumentation (Node.js)

Mandatory for Node.js AI integrations. OTel only patches when the package is imported (zero cost if unused).

Steps

  1. Add to getAutoPerformanceIntegrations() in packages/node/src/integrations/tracing/index.ts — LangChain MUST come first
  2. Add to getOpenTelemetryInstrumentationToPreload() for OTel-based integrations
  3. Export from packages/node/src/index.ts: integration function + options type
  4. Add E2E tests:

- Node.js: dev-packages/node-integration-tests/suites/tracing/{provider}/ - Cloudflare: dev-packages/cloudflare-integration-tests/suites/tracing/{provider}/ - Browser: dev-packages/browser-integration-tests/suites/tracing/ai-providers/{provider}/

Key Rules

  1. Respect sendDefaultPii for recordInputs/recordOutputs
  2. Set SEMANTIC_ATTRIBUTE_SENTRY_ORIGIN = 'auto.ai.{provider}' (alphanumerics, _, . only)
  3. Truncate large data with helper functions from utils.ts
  4. gen_ai.invoke_agent for parent ops, gen_ai.chat for child ops

Checklist

  • Runtime-specific code placed only in that runtime's package
  • Added to getAutoPerformanceIntegrations() in correct order (Node.js)
  • Added to getOpenTelemetryInstrumentationToPreload() (Node.js with OTel)
  • Exported from appropriate package index
  • E2E tests added and verifying auto-instrumentation
  • Only used attributes from Sentry Gen AI Conventions
  • JSDoc says "enabled by default" or "not enabled by default"
  • Documented how to disable (if auto-enabled)
  • Verified OTel only patches when package imported (Node.js)

Reference Implementations

  • Pattern 1 (Span Processors): packages/node/src/integrations/tracing/vercelai/
  • Pattern 2 (Client Wrapping): packages/node/src/integrations/tracing/openai/
  • Pattern 3 (Callback/Hooks): packages/node/src/integrations/tracing/langchain/

When in doubt, follow the pattern of the most similar existing integration.

适合场景

01

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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

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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

32.85%
按下载量换算21

Claude

27.97%
按下载量换算18

Cursor

19.49%
按下载量换算12

Gemini CLI

10.28%
按下载量换算6

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

操作浏览器

该 Skill 可能涉及浏览器控制能力,使用时可能读取或操作网页内容,需要在受控环境中确认权限边界。

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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