skills.rest
radrad
radradCOMMUNITY
Explore all skills by this author →
GitHub

troubleshoot

Analyzes debug JSONL logs to explain delays, tool usage, and load failures.

Updated Mar 17, 2026
Search Tags:#debugging#logs#troubleshoot#jsonl#copilot-chat
One-click install
npx skills add https://github.com/radrad/vscode-copilot-chat --skill troubleshoot-radrad
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: troubleshoot
Source: https://github.com/radrad/vscode-copilot-chat/tree/main/assets/prompts/skills/troubleshoot
Command: npx skills add https://github.com/radrad/vscode-copilot-chat --skill troubleshoot-radrad

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill helps operators understand why a chat agent behaved unexpectedly by analyzing direct log files and grounding conclusions in evidence rather than guesswork.

Core Features & Use Cases

  • Reads and interprets debugging JSONL logs to identify causes of slow responses, unintended tool usage, or loading failures.
  • Provides evidence-based explanations suitable for troubleshooting, post-mortems, and debugging sessions.
  • Use cases include questions like why a request was slow, why a tool or subagent was invoked, or why instructions did not load correctly.

Quick Start

Load the current session's debug log and ask the AI to explain delays, tool usage, or load failures.

Frequently Asked Questions about troubleshoot

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

FAQPage Schema
How do I debug why my chat agent was slow to respond?▼

Debug slow chat responses by loading JSONL debug logs for analysis. The skill interprets raw log traces to pinpoint delay causes, providing evidence-based explanations rather than guesswork for troubleshooting.

What is the best way to troubleshoot unintended tool usage in a chat agent?▼

Troubleshoot unintended tool usage by examining debug JSONL logs to trace agent decisions. The skill investigates log traces to explain why specific tools or subagents were invoked, supporting findings with direct log entries.

Why did my chat agent instructions fail to load correctly?▼

Instruction load failures can be diagnosed by analyzing JSONL debug logs for error traces. The skill reads log files to identify why instructions did not load correctly, grounding conclusions in direct log entries.

Can I use JSONL logs to investigate copilot-chat behavior issues?▼

Yes, JSONL logs can be used to investigate copilot-chat behavior issues. The skill interprets debug log files to provide evidence-based explanations for unexpected agent behavior, suitable for post-mortems and debugging sessions.

Does this debugging approach work without additional dependencies?▼

Yes, this debugging approach works without additional dependencies. The skill requires only JSONL debug log files from your current session to analyze chat agent behavior and provide evidence-based troubleshooting explanations.

Related Skills

Explore More Software Engineering Skills→
aresbitaresbit
46

session-logs

Search and analyze historical session JSONL files using jq and rg.

Community
Intermediate
mandubianmandubian
1

debugger.default

Isolate software failure root causes and propose targeted fixes.

Community
Advanced
Yeachan-HeoYeachan-Heo
38.5k

trace

Visualize agent flow traces and summaries to diagnose execution paths.

Community
Basic
sky770825sky770825

session-cleaner

Convert raw OpenClaw and Clawdbot session JSONL logs into markdown transcripts.

Community
Intermediate