pitfall-capture

To document BERDL data analysis pitfalls, the skill systematically captures errors, incorrect results, and data surprises, then drafts actionable entries with code examples directly into the shared `docs/pitfalls.md` knowledge base.

The best way to capture query failures is to check for existing documentation and draft new knowledge base entries that record the exact error, incorrect and correct query patterns, and suggested solutions for future reference.

Error documentation prevents repeated mistakes by systematically identifying, recording, and sharing pitfalls encountered during data analysis workflows, ensuring common problems are available with actionable solutions for future users.

Yes, you can record performance issues and data surprises. The skill captures and formats details about errors, unexpected results, performance issues, or data anomalies, creating entries if the issue is novel.

When a complex BERDL query fails, you should use the skill to document the exact error, contrast the incorrect and correct query patterns, and suggest a solution to be added to the shared knowledge base.

A limitation of automated error documentation is that it relies on checking existing knowledge base entries to determine novelty, meaning undocumented or subtle data surprises might require manual review before drafting new pitfalls.