Scans source trees to catalog errors and flag inconsistencies.
npx skills add https://github.com/hamzaPixl/pixl-ai --skill error-catalog
Please help me install this Agent Skill. Skill: error-catalog Source: https://github.com/hamzaPixl/pixl-ai/tree/main/packages/crew/skills/error-catalog Command: npx skills add https://github.com/hamzaPixl/pixl-ai --skill error-catalog
Engineers and DevOps struggle to understand and harmonize error handling across services, leading to inconsistent messages, debugging delays, and fragile client integrations.
Provide the path to your service directory to scan, catalog errors, detect inconsistencies, and generate an error report.
High-intent search queries and answers about installing and using this skill.
To catalog service errors, scan your backend source trees to discover thrown exceptions, error classes, and HTTP mappings. This generates a unified error catalog with codes and messages, while flagging inconsistencies like missing error codes and mismatched HTTP statuses.
Detecting inconsistent HTTP status mappings and leaking client messages requires scanning your source code for error patterns. An inconsistency analysis flags these issues by auditing thrown exceptions and validation errors against your standardized error catalog.
Yes, you can scan typical source trees like app directories in Node.js and Python backends. By providing a path for optional scoping, the analysis discovers validation errors and thrown exceptions to map them into a structured catalog.
To generate standardized error infrastructure, the cataloging process optionally scaffolds base classes, enums, and handlers. This creates a unified error baseline, ensuring consistent error codes, messages, and HTTP mappings across your API services.
Mismatched HTTP statuses and missing error codes occur when thrown exceptions are not centrally cataloged. Scanning your source directories detects these inconsistencies by auditing your error classes and validation issues against a unified standard.
No, you do not need to manually map error codes to HTTP statuses beforehand. The analysis discovers existing thrown exceptions and HTTP mappings automatically, identifying missing codes and generating a structured catalog with proper mappings.
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