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TalonT-OrgTalonT-Org/AutoSkillit/.claude/skills/audit-bugs/SKILL.md

audit-bugs

Skill5 starsChanged 6 months agoMITView on GitHub

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".

1 other project uses a version of this.

Adopted by

Most recently taken up by

The file

We split this skill into the rules it gives an agent

11 rules. About 0 are common, 5 are distinctive, and 6 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈5

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 6

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Very specific:

    Create files outside temp/audit-bugs/ directory

    line 31
  2. Distinctive:

    Use subagents heavily for parallel log analysis

    line 34
  3. Very specific:

    All output goes under temp/audit-bugs/ (create if needed)

    line 35
  4. Distinctive:

    Do not change any code

    line 38
  5. Very specific:

    Verify the directory exists and contains .jsonl files.

    line 55
  6. Very specific:

    Use find with -newermt to filter .jsonl files modified since the target date

    line 59
  7. Very specific:

    Look for tool calls writing to temp/investigate/investigation_*.md or temp/rectify/rectify_*.md for structured findings

    line 78
  8. Distinctive:

    Search for keywords: "root cause", "Root Cause", "fix", "summary", "finding"

    line 79
  9. Distinctive:

    Read the first ~500 lines for context, then search for conclusions

    line 80
  10. Distinctive:

    After subagents return, group findings into recurring patterns:

    line 84
  11. Very specific:

    Ensure temp/audit-bugs/ exists (mkdir -p).

    line 96

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
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

  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 '/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 temp/investigate/investigation_*.md or 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 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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