Agent skill
audit-bugs
Analyze historical bug patterns by mining Claude Code project logs for /investigate skill invocations since a specified date. Identifies recurring root causes, architectural gaps, and proactive detection strategies. Use when user says "audit bugs", "bug patterns", "analyze investigations", or "bug audit".
Install this agent skill to your Project
npx add-skill https://github.com/majiayu000/claude-skill-registry/tree/main/skills/other/other/audit-bugs-trecek-useful-claude-skills
SKILL.md
Bug Pattern Audit Skill
Mine Claude Code conversation logs for /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
temp/audit-bugs/directory
ALWAYS:
- Use subagents heavily for parallel log analysis
- All output goes under
temp/audit-bugs/(create if needed) - Final report:
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
- Use
findwith-newermtto filter.jsonlfiles modified since the target date - From those,
grep -l '"skill".*"investigate"'to find files where the investigate skill was invoked (tool invocation pattern) - Also
grep -l '/investigate'to catch user-typed invocations - 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
temp/investigate/investigation_*.mdortemp/rectify/rectify_*.mdfor 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:
- Identify bugs that share the same root architectural weakness
- Count frequency of each pattern across sessions
- 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 temp/audit-bugs/ exists (mkdir -p).
Save to: 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.
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