troubleshootlisted

Investigate unexpected chat agent behavior by analyzing direct debug logs in JSONL files. Use when users ask why something happened, why a request was slow, why tools or subagents were used or skipped, or why instructions/skills/agents did not load.
Pointa-Labs/basehalf · ★ 15 · AI & Automation · score 73

Install: claude install-skill Pointa-Labs/basehalf

# Troubleshoot ## Purpose This skill investigates and explains unexpected chat agent behavior using direct log files. Use this skill for questions like: - Why did this request take so long? - Why was a tool or subagent called? - Why did instruction/skill/agent files not load? - Why was a tool call blocked or failed? - Why did the model not follow expectations? Base conclusions on evidence from logs. Do not guess. ## Data Source - Target session log directory/directories for analysis: `{{VSCODE_TARGET_SESSION_LOG}}` Use direct debug log files written by Copilot Chat: ``` debug-logs/<sessionId>/ main.jsonl — always start here; primary conversation log models.json — (optional) snapshot of available models at session start system_prompt_0.json — (optional) full system prompt sent to the model (untruncated) system_prompt_1.json — (optional) written when the model changes mid-session tools_0.json — (optional) tool definitions sent to the model tools_1.json — (optional) written when the model changes mid-session runSubagent-<agentName>-<uuid>.jsonl — (optional) subagent's tool calls & LLM requests searchSubagent-<uuid>.jsonl — (optional) search subagent work title-<uuid>.jsonl — (optional, UI-only) title generation categorization-<uuid>.jsonl — (optional, UI-onl