Error Diagnosis#

Analyze error messages, stack traces, and log output to diagnose root causes and suggest fixes. Use when debugging crashes, runtime errors, build failures, or unexpected behavior.

Usage#

text

Diagnose this error: [paste error message or stack trace]

Or with context:

text

Diagnose: [error]. Language: [lang]. Framework: [framework]. Recent changes: [what changed].

How It Works#

1. Parse — extract error type, message, file locations, line numbers from raw output
2. Classify — categorize the error (syntax, runtime, dependency, config, permission, network, OOM, etc.)
3. Trace — follow the call stack to identify the originating code vs. where the error surfaced
4. Diagnose — determine root cause using error patterns, common pitfalls, and framework-specific knowledge
5. Fix — provide actionable fix with code snippets

Supported Error Sources#

• Stack traces: Python, JavaScript/Node.js, Java, Go, Rust, C/C++, Ruby, PHP
• Build errors: npm, pip, cargo, gradle, maven, webpack, vite, tsc
• Runtime errors: segfaults, OOM, deadlocks, race conditions, type errors
• Infrastructure: Docker, Kubernetes, systemd, nginx, database connection errors
• CI/CD: GitHub Actions, GitLab CI, CircleCI failure logs

Output Format#

markdown

## Error Type
[Classification: e.g., "TypeError — accessing property of undefined"]

## Root Cause
[1-2 sentences explaining WHY this happened]

## Fix
[Code snippet or command to resolve]

## Prevention
[How to avoid this in the future: type check, test, lint rule, etc.]

Advanced Features#

Multi-Error Analysis#

Paste multiple errors — the skill identifies whether they share a root cause or are independent issues.

Regression Detection#

text

This error started after [commit/change]. Analyze whether the change could cause this.

Environment Comparison#

text

Works in dev, fails in prod. Error: [error]. Dev config: [config]. Prod config: [config].

Scripts#

scripts/parse_stacktrace.py#

Extracts structured data from raw stack traces:

bash

python3 scripts/parse_stacktrace.py < error.log

Returns JSON with error type, message, frames (file, line, function), and suggested search queries.