Audit Bugs

Bug Pattern Audit Skill

Mine Claude Code conversation logs for /autoskillit:investigate skill invocations to identify recurring bug patterns, architectural gaps, and proactive detection strategies.

When to Use

• User says "audit bugs", "bug patterns", "analyze investigations", or "bug audit"
• User wants to find recurring themes across past bug investigations
• User wants proactive strategies to catch bugs before they manifest

Arguments

The user may provide a "since" date (e.g., 2/7, 2026-02-07, last week). If not specified, use AskUserQuestion to ask what the earliest lookback date should be before proceeding.

Critical Constraints

NEVER:

• Modify any source code files
• Create files outside {{AUTOSKILLIT_TEMP}}/audit-bugs/ directory
• Run subagents in the background (run_in_background: true is prohibited)

ALWAYS:

• Use subagents heavily for parallel log analysis
• All output goes under {{AUTOSKILLIT_TEMP}}/audit-bugs/ (create if needed)
• Final report: {{AUTOSKILLIT_TEMP}}/audit-bugs/bug_pattern_audit_{YYYY-MM-DD_HHMMSS}.md
• Subagents must NOT create their own files - they return findings in their response text only
• Do not change any code

Workflow

Step 1: Locate Project Logs

Claude Code stores conversation logs at ~/.claude/projects/ in a folder derived from the project's absolute path with / replaced by -.

Derive the log directory:

# Convert current working directory to Claude's folder naming scheme
PROJECT_PATH=$(pwd)
LOG_DIR="$HOME/.claude/projects/-${PROJECT_PATH//\//-}"
# Remove leading double dash if present
LOG_DIR="${LOG_DIR//--/-}"

Verify the directory exists and contains .jsonl files.

Step 2: Filter by Date and Investigate Skill

1. Use find with -newermt to filter .jsonl files modified since the target date
2. From those, grep -l '"skill".*"investigate"' to find files where the investigate skill was invoked (tool invocation pattern)
3. Also grep -l '/autoskillit:investigate' to catch user-typed invocations
4. Combine and deduplicate. Only use top-level files (not subagent logs under */subagents/)

Step 3: Dispatch Subagents for Parallel Analysis

Split the matching files into batches of ~5 and dispatch general-purpose subagents in parallel. Each subagent should extract from each log file:

• Error/Symptom: The error message or failure the user reported
• Root Cause: What the investigation identified as the root cause
• Component: Which module/system was affected
• Category: Bug classification (e.g., "type boundary", "state management", "validation gap")
• Fix: What solution was identified or applied

Subagent instructions for reading logs:

• JSONL format: each line is a JSON object
• "type": "human" entries contain user messages (error reports)
• "type": "assistant" entries with text content contain investigation findings
• Look for tool calls writing to {{AUTOSKILLIT_TEMP}}/investigate/investigation_*.md or {{AUTOSKILLIT_TEMP}}/rectify/rectify_*.md for structured findings
• Search for keywords: "root cause", "Root Cause", "fix", "summary", "finding"
• Read the first ~500 lines for context, then search for conclusions

Step 4: Synthesize Patterns

After subagents return, group findings into recurring patterns:

1. Identify bugs that share the same root architectural weakness
2. Count frequency of each pattern across sessions
3. For each pattern, identify:
   • Which components it affects
   • Why it keeps recurring
   • What architectural gap enables it
   • Concrete grep/search patterns that could detect latent instances today

Step 5: Write Report

Ensure {{AUTOSKILLIT_TEMP}}/audit-bugs/ exists (mkdir -p).

Save to: {{AUTOSKILLIT_TEMP}}/audit-bugs/bug_pattern_audit_{YYYY-MM-DD_HHMMSS}.md

Structure:

# Bug Pattern Audit: Investigations Since {date}

**Analysis Date:** {today}
**Sessions Analyzed:** {count}

## Executive Summary
{2-3 sentences: top patterns, frequency, recommended investments}

## Pattern N: {Name}
**Frequency:** X of Y sessions (Z%)

### Manifestations
| Session | Date | Bug | Component |
{table of affected sessions}

### Root Architectural Gap
{Why this pattern keeps occurring}

### Proactive Detection Strategy
{Concrete scans, tests, or grep patterns to find latent instances}

---

## All Sessions Quick Reference
| # | Session ID | Date | Error Summary | Pattern(s) |
{table of all sessions}

## Recommended Proactive Scans
{Runnable grep/rg commands to find latent bugs today}

Step 6: Terminal Summary

Output a concise summary: pattern count, top 3 patterns by frequency, and report location.