How does this skill find the relevant requirements?

The skill uses grep and glob tools to search your project's documentation for specific requirement IDs (REQ-*) that match the tags found in production alerts.

Can it analyze recent code changes?

Yes, it uses git history analysis to identify recent commits associated with the problematic requirement, helping to pinpoint potential regressions.

What is a Remediation Intent?

It is a structured document created by the skill that defines the problem, root cause hypothesis, and success criteria for fixing a specific production issue.

Does this skill automatically fix the production code?

No, it focuses on the diagnostic and documentation phase, providing the necessary context and clear instructions for a developer or AI agent to implement the fix safely.

Trace Production Issue

Name: Trace Production Issue
Author: foolishimp

byfoolishimp

Analíticas y Monitorización

Traces production alerts back to original requirements and generates actionable remediation intents to close the SDLC feedback loop.

Acerca de

This skill bridges the gap between production operations and development by automating the path from runtime failure to actionable intent. When a production alert occurs, it enables Claude to parse the alert data, trace it back to specific business requirements (REQ-IDs), and identify the original development intent. By analyzing the implementing code and recent git history, the skill generates a comprehensive Remediation Intent that documents root causes and success criteria, ensuring that every production issue is systematically integrated back into the software development lifecycle.

Características Principales

Automated requirement tracing from production alert metadata
Traceability logging for SDLC feedback loop closure
0 GitHub stars
Identification of original project intent and implementing source code
Standardized generation of Remediation Intents (INT-*)
Git history analysis for regressions related to specific requirements

Casos de Uso

Root cause analysis for production errors by tracing back to specific commits
Resolving SLA violations by mapping performance alerts to NFR requirements
Automating the creation of remediation tasks from monitoring system triggers

Acerca de

Características Principales

Automated requirement tracing from production alert metadata
Traceability logging for SDLC feedback loop closure
0 GitHub stars
Identification of original project intent and implementing source code
Standardized generation of Remediation Intents (INT-*)
Git history analysis for regressions related to specific requirements

Casos de Uso

Root cause analysis for production errors by tracing back to specific commits
Resolving SLA violations by mapping performance alerts to NFR requirements
Automating the creation of remediation tasks from monitoring system triggers