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sentry-setup-ai-monitoring

Detect installed AI SDKs and configure Sentry AI monitoring for JavaScript and Python projects.

Updated Mar 2, 2026
Search Tags:#python#javascript#langchain#openai#sentry#ai monitoring#llm observability
One-click install
npx skills add https://github.com/DMT123/claude-skills-collection --skill sentry-setup-ai-monitoring-dmt123
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: sentry-setup-ai-monitoring
Source: https://github.com/DMT123/claude-skills-collection/tree/main/plugins/sentry/sentry-setup-ai-monitoring
Command: npx skills add https://github.com/DMT123/claude-skills-collection --skill sentry-setup-ai-monitoring-dmt123

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) components.

What problem does it solve?

This Skill simplifies the process of integrating Sentry's AI monitoring into your project, allowing you to track LLM calls, agent executions, and token consumption.

Core Features & Use Cases

  • Automated SDK Detection: Automatically identifies installed AI SDKs (OpenAI, Anthropic, LangChain, etc.) in JavaScript and Python projects.
  • Version Verification: Checks if your Sentry SDK version meets the minimum requirements for AI monitoring.
  • Configuration Guidance: Provides explicit code examples for integrating Sentry with various AI SDKs.
  • Manual Instrumentation: Offers detailed instructions for manual span creation if automatic detection fails.
  • Use Case: You've built a chatbot using LangChain and want to monitor its LLM interactions, tool usage, and costs. This skill will guide you through setting up Sentry to capture all that data automatically.

Quick Start

Use the sentry-setup-ai-monitoring skill to automatically detect and configure Sentry AI monitoring for your project.

Frequently Asked Questions about sentry-setup-ai-monitoring

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I set up Sentry AI monitoring for a LangChain project?▼

Setting up Sentry AI monitoring for LangChain involves configuring Sentry integrations to automatically detect installed SDKs and capture LLM calls, agent executions, and token usage. This process provides explicit code examples for integration.

Can I track OpenAI token usage automatically with Sentry in Python?▼

Yes, you can track OpenAI token usage automatically with Sentry in Python by configuring Sentry's AI monitoring integrations. The system detects installed AI libraries and instruments them to capture token consumption metrics.

What AI SDKs are supported by Sentry for LLM observability?▼

Sentry supports LLM observability for OpenAI, Anthropic, Vercel AI, LangChain, Google GenAI, and Hugging Face Hub in JavaScript and Python projects. The system detects installed SDKs for automatic and manual instrumentation.

Does Sentry AI monitoring work with JavaScript and Python projects?▼

Yes, Sentry AI monitoring works with both JavaScript and Python projects. It automates SDK detection and configuration across both languages to track LLM interactions, agent executions, and token consumption metrics.

Why is my Sentry AI monitoring not capturing LLM calls automatically?▼

Sentry AI monitoring may fail to capture LLM calls automatically if your Sentry SDK version does not meet minimum requirements or if automatic detection fails. You can use manual span creation to track interactions as a fallback.

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