Structured error knowledge database for AI coding agents. 2632 error patterns across 54 domains (android, api, aws, banking, cicd, cloud, cmake, communication, cuda, culture, data, database, disaster, docker, dotnet, elasticsearch, embedded, emergency, flutter, food-safety, git, go, grpc, huggingfa…
Everything here was measured by our prober or read from a registry. Nothing is self-reported.
Not distributed through a package registry we index.
Attributed to the source that supplied each field. Treated as claims, not facts.
Structured error knowledge database for AI coding agents. 2632 error patterns across 54 domains (android, api, aws, banking, cicd, cloud, cmake, communication, cuda, culture, data, database, disaster, docker, dotnet, elasticsearch, embedded, emergency, flutter, food-safety, git, go, grpc, huggingface, java, kafka, kubernetes, legal, llm, medical, mental-health, mongodb, networking, nextjs, nginx, node, opencv, pet-safety, php, pip, policy, python, pytorch, react, redis, ros2, rust, safety, security, tensorflow, terraform, typescript, unity, visa). Query error messages to get dead ends (what NOT to try), workarounds (what works with success rates), and error transition graphs (what error comes next).
Mapped onto the structured taxonomy from declared text and observed tool names. Confidence shown for derived entries.
Every source is kept verbatim. Field changes are logged as events.