Error Detective

The error-detective skill acts as a specialized diagnostic tool for AI agents, focusing on identifying and resolving code execution failures. It analyzes runtime logs and stack traces to pinpoint the root cause of bugs within a project's logic or dependencies.

When to use it

• Debugging unexpected crashes in a live development environment where standard logging is insufficient.
• Investigating complex integration errors between different microservices or third-party APIs.
• Validating that recent code changes have not introduced regressions in critical user workflows.
• Automating the triage process for error reports submitted by end-users without immediate developer intervention.

Key capabilities

• Parses raw stack traces and console logs to extract actionable error messages.
• Correlates specific lines of code with failure points based on execution context.
• Generates human-readable summaries explaining why an operation failed.
• Suggests potential fixes or workarounds based on the identified error type.

Example prompts

• "Analyze this stack trace from our production server and explain the root cause of the NullPointerException."
• "Review the recent deployment logs to identify any new errors introduced after the latest feature update."
• "Detect if the API timeout error is caused by network latency or a server-side issue based on these logs."

Tips & gotchas

Ensure you provide complete, unredacted log files containing stack traces for the skill to perform an accurate diagnosis. The tool relies heavily on the quality of the input data; fragmented logs may lead to incomplete analysis.