Analytics & Monitoring Agent Skills for Zed

Debug AI traces, find exceptions, analyze sessions, and manage prompts via Langfuse MCP.

Render a full AWS transaction trace as an interactive HTML timeline from an X-Ray trace ID.

Discovers user intent and generates a structured, step-by-step plan for model customization workflows.

Generates code that fine-tunes a base model using SageMaker serverless training jobs.

Azure Monitor Ingestion SDK for Python. Use for sending custom logs to Log Analytics workspace via Logs Ingestion API.

Azure Monitor OpenTelemetry Distro for Python.

Azure Monitor OpenTelemetry Exporter for Python.

Auto-instrument Node.js applications with distributed tracing, metrics, and logs.

Azure Monitor Query SDK for Python. Use for querying Log Analytics workspaces and Azure Monitor metrics.

Azure Application Insights SDK for .NET.

Backtest crypto and traditional trading strategies against historical

Collect BambooHR debug evidence for support tickets and troubleshooting.

Agent-ready Bambu print monitoring with exact plate previews and start/finish payloads.

Use when setting up log aggregation solutions using ELK, Loki, or Splunk.

Use for BayeSED3 SED work — galaxy or AGN fitting, prior setup, Results and posterior plots, Bayesian evidence or model-configuration…

Applies Bayesian reasoning to systematically update probability estimates with new evidence, helping make better forecasts and avoid…

Complete bearing fault diagnostic workflow using vibration analysis and the predictive-maintenance-mcp server.

Executes elements whose implementation is a python:// entry point, with the study's dependencies installed.

Benchmark a model served on MAX with the `max benchmark` command: measure throughput (tokens/sec), latency (TTFT, TPOT, inter-token…

Find, inspect, and check AI benchmark records with the Benchmark Radar CLI.

Runs an honest before/after evaluation of any change — a model prompt, an algorithm, a feature, or a refactor — against a fair baseline…