Is it compatible with external monitoring tools?

Yes, the traceability patterns are designed to be included in logs and metrics for tools like Datadog or Prometheus, enabling backward-traceability from production alerts.

Which requirement types does it support?

It supports Functional Requirements (REQ-F), Non-Functional Requirements (REQ-NFR), Data Quality Requirements (REQ-DATA), and Business Rules (REQ-BR).

What is the primary purpose of this skill?

It defines a standardized way to label and trace requirements through every stage of development, from documentation and design to implementation and runtime monitoring.

Can I use this skill to find untested requirements?

Yes, the skill includes query operations to identify coverage gaps by comparing the requirements defined in your docs against implemented code and tests.

How do I tag my code using this skill?

You can use standardized comments like '# Implements: REQ-F-AUTH-001' in your source code or '# Validates: REQ-F-AUTH-001' in your test files to enable automated tracing.

Requirement Traceability & AI SDLC

Name: Requirement Traceability & AI SDLC
Author: foolishimp

byfoolishimp

0•

Security & Testing

Standardizes requirement key patterns and automates traceability across the entire software development lifecycle.

The Requirement Traceability skill provides a foundational framework for the AI SDLC, enabling developers to define, validate, and trace functional, non-functional, data, and business requirements. By establishing rigid key patterns (REQ-*) and tagging conventions, it bridges the gap between initial intent and runtime telemetry. This skill is essential for ensuring code coverage, simplifying audits, and facilitating backward-traceability from production alerts back to original business requirements, making it a cornerstone for high-integrity AI-assisted engineering.

Key Features

010 GitHub stars

02Definition and validation of REQ-* key patterns for functional, data, and non-functional requirements.

03Structured tagging conventions for code implementation (# Implements) and test validation (# Validates).

04Automated extraction of requirement keys from source code, commits, and documentation.

05Support for nested sub-keys to disambiguate complex business rules, constraints, and formulas.

06Bi-directional traceability linking business intent to code, tests, and runtime metrics.

Use Cases

01Mapping high-level business requirements to specific code blocks and unit tests for audit readiness.

02Performing impact analysis by tracing code changes back to their original functional requirements.

03Identifying coverage gaps where defined requirements lack corresponding implementation or validation tests.

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add foolishimp/ai_sdlc_method core

For use in Claude.ai and ChatGPT

Download Skill