What tools does this skill support for monitoring?

This skill supports LangSmith for tracing, Prometheus for metrics, OpenTelemetry for distributed tracing, and Grafana for visualization and dashboards.

Can I use this for self-hosted LangChain environments?

Yes, the skill includes configurations for self-hosted LangSmith endpoints and local Prometheus/Grafana infrastructure.

Does it track LLM token usage and costs?

Yes, it includes Prometheus counters and alerting rules specifically designed to track token usage and trigger alerts when budgets are exceeded.

How does it handle errors in LLM chains?

It implements structured logging and Prometheus metrics to track error rates and types, allowing you to set up alerts for high failure rates.

How do I trigger this skill in Claude Code?

You can trigger it using natural language phrases like 'set up langchain monitoring', 'enable langchain tracing', or 'configure langchain observability'.

LangChain Observability

Name: LangChain Observability
Author: Brmbobo

byBrmbobo

0•

분석 및 모니터링

Implements comprehensive monitoring, tracing, and alerting for LangChain applications using LangSmith, Prometheus, and OpenTelemetry.

This skill provides a complete framework for monitoring the health, performance, and cost of LangChain-based AI applications. It enables deep visibility into LLM chains through LangSmith tracing, real-time performance tracking with Prometheus metrics, distributed tracing via OpenTelemetry, and structured JSON logging. By automating the setup of Grafana dashboards and proactive alerting rules, it helps developers detect high latency, elevated error rates, or unexpected token usage before they impact production users.

주요 기능

01OpenTelemetry integration for distributed system tracing

02Automated LangSmith tracing for deep chain inspection

030 GitHub stars

04Pre-configured Grafana dashboards and Prometheus alerting rules

05Real-time Prometheus metrics for latency, request rates, and token usage

06Structured JSON logging for enhanced log analysis and debugging

사용 사례

01Monitoring production LLM application health and performance

02Tracking and optimizing token usage costs across different models

03Debugging complex LangChain sequences with distributed tracing

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add brmbobo/web2podcast langchain-observability

For use in Claude.ai and ChatGPT

Download Skill