home / skills / yonatangross / orchestkit / errors
This skill analyzes error patterns from Claude Code sessions to deliver actionable fixes and root-cause insights.
npx playbooks add skill yonatangross/orchestkit --skill errorsReview the files below or copy the command above to add this skill to your agents.
---
name: errors
license: MIT
compatibility: "Claude Code 2.1.34+. Requires memory MCP server."
description: Error pattern analysis and troubleshooting for Claude Code sessions. Use when handling errors, fixing failures, troubleshooting issues.
context: inherit
agent: debug-investigator
version: 1.0.0
author: OrchestKit
tags: [errors, debugging, troubleshooting, patterns]
user-invocable: false
allowed-tools: [Read, Bash, Grep]
complexity: low
metadata:
category: document-asset-creation
mcp-server: memory
---
# Error Pattern Analysis
Analyze errors captured from Claude Code sessions to identify patterns and get actionable insights.
## Quick Start
```bash
/errors # Batch analysis of historical error patterns
/debug # CC 2.1.30 real-time debug for current session
```
### When to Use Which
| Command | Purpose | Scope |
|---------|---------|-------|
| `/errors` | Batch analysis of error patterns (last 24h/7d) | Historical patterns |
| `/debug` | Real-time debug of current session state | Current session |
| `/ork:fix-issue` | Full RCA workflow for specific bug | Single issue |
## Quick Analysis
```bash
# Run batch analysis on last 24h of errors
python .claude/scripts/analyze_errors.py
# Analyze last 7 days
python .claude/scripts/analyze_errors.py --days 7
# Generate markdown report
python .claude/scripts/analyze_errors.py --report
```
## What Gets Captured
The error collector hook captures:
- Tool name (Bash, mcp__memory__search_nodes, etc.)
- Error message (first 500 chars)
- Tool input (command/query that failed)
- Timestamp and session ID
**Location:** `.claude/logs/errors.jsonl`
## Current Error Rules
Check learned patterns that trigger warnings:
```bash
cat .claude/rules/error_rules.json | jq '.rules[] | {id, signature, count: .occurrence_count}'
```
## Files
| File | Purpose |
|------|---------|
| `.claude/hooks/posttool/error-collector.sh` | Captures errors to JSONL |
| `.claude/hooks/pretool/bash/error-pattern-warner.sh` | Warns before risky commands |
| `.claude/scripts/analyze_errors.py` | Batch pattern analysis |
| `.claude/rules/error_rules.json` | Learned error patterns |
| `.claude/logs/errors.jsonl` | Raw error log |
## Common Patterns
### PostgreSQL Connection Errors
```
pattern: role "X" does not exist
fix: Use Docker connection: docker exec -it orchestkit-postgres-dev psql -U orchestkit_user -d orchestkit_dev
pattern: relation "X" does not exist
fix: Check MCP postgres server connection string - may be connected to wrong database
```
## Related Skills
- fix-issue: Fix identified errors
- debug-investigator: Debug error root causes
## Adding New Rules
Rules are auto-generated by `analyze_errors.py` when patterns repeat 2+ times.
For manual rules, edit `.claude/rules/error_rules.json`:
```json
{
"id": "custom-001",
"pattern": "your regex pattern",
"signature": "human readable signature",
"tool": "Bash",
"occurrence_count": 1,
"fix_suggestion": "How to fix this"
}
```This skill performs error pattern analysis and troubleshooting for Claude Code sessions, surfacing recurring failures and actionable fixes. It captures runtime errors, learns common signatures, and produces reports or real-time warnings to speed diagnosis and remediation.
An error-collector hook records tool name, truncated error message, input that triggered the failure, timestamp, and session ID into a JSONL log. Batch analysis scripts scan recent logs to cluster repeated patterns, auto-generate rules when patterns repeat, and emit human-friendly fix suggestions or warnings for risky commands. A real-time debug endpoint inspects the current session state and flags matching rules immediately.
How are error patterns detected?
Patterns are identified by clustering repeated error signatures in the JSONL logs; scripts mark a pattern when it repeats two or more times and optionally add a fix suggestion.
Where are errors stored and how do I inspect them?
Errors are written to a centralized JSONL log (errors.jsonl) with tool, truncated message, input, timestamp, and session ID; you can query this file or run the batch analyzer to generate reports.