What makes this different from default Claude Code telemetry?

While default telemetry provides basic OTEL data, this skill uses 10 specific hooks to capture granular details like tool sequences, subagent types, and context compaction events.

Does this require external services?

Yes, it is designed to work with a local Loki and Grafana setup for data storage and visualization, though it can be adapted for other logging backends.

Will these hooks slow down my Claude Code sessions?

The hooks run as lightweight Python scripts, resulting in negligible performance impact on your active development workflow.

How do I view the captured data?

You can view data through the included Grafana dashboard templates or by running custom LogQL queries against your Loki instance.

Enhanced Telemetry for Claude Code

Name: Enhanced Telemetry for Claude Code
Author: adaptationio

byadaptationio

분석 및 모니터링

Captures comprehensive AI session metrics and tool usage patterns through 10 deep-instrumentation hooks for advanced observability.

소개

This skill provides deep observability for Claude Code by instrumenting all 10 available system hooks to capture granular data on sessions, subagents, tool sequences, and context utilization. It extends beyond standard OTEL telemetry to offer detailed analytics on prompt patterns, token usage, and repository-specific activity. Designed for developers and teams who need to monitor AI behavior, audit costs, or optimize their local LLM workflows, it integrates seamlessly with Loki and includes pre-configured Grafana dashboards for immediate visual analysis of AI-assisted coding sessions.

주요 기능

Detailed tracking of subagent spawning, types, and completion status
Comprehensive instrumentation of all 10 Claude Code system hooks
Deep tool analysis including sequences, error rates, and response sizes
Pre-built Grafana dashboards for visual session and repository analytics
0 GitHub stars
Advanced context monitoring with token estimation and window utilization

사용 사례

Optimizing developer workflows by analyzing tool usage patterns and success rates
Auditing AI token consumption and context window efficiency to manage API costs
Debugging complex multi-step tasks by visualizing subagent and tool sequences

소개

주요 기능

Detailed tracking of subagent spawning, types, and completion status
Comprehensive instrumentation of all 10 Claude Code system hooks
Deep tool analysis including sequences, error rates, and response sizes
Pre-built Grafana dashboards for visual session and repository analytics
0 GitHub stars
Advanced context monitoring with token estimation and window utilization

사용 사례

Optimizing developer workflows by analyzing tool usage patterns and success rates
Auditing AI token consumption and context window efficiency to manage API costs
Debugging complex multi-step tasks by visualizing subagent and tool sequences