Can it find rules hidden in databases?

Yes, it performs cross-cutting discovery which includes scanning migration files and schemas for database-level constraints and triggers.

Does Spec Extract document API endpoints or infrastructure?

No, it specifically ignores infrastructure concerns like logging, metrics, and network calls to focus exclusively on domain logic and business rules.

How does the skill handle large codebases?

It uses a clustering approach to find relevant code symbols first. For very large concepts, you can use the --broad flag to increase the search cap and produce a lightweight index.

What is the primary difference between spec-extract and spec-create?

Spec-extract reverse-engineers existing code to document how the system currently works, whereas spec-create is used to design new features and requirements from scratch.

What tools are required for the best extraction quality?

While it can fall back to Grep, Spec Extract works best with the 'cartog' tool installed to perform deep code intelligence and symbol tracing.

Spec Extract: Business Rule Discovery

Name: Spec Extract: Business Rule Discovery
Author: jrollin

byjrollin

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Aprendizaje y Documentación

Extracts structured business rules and domain logic from existing codebases using automated code intelligence and LLM analysis.

Spec Extract is a specialized capability designed for developers and business analysts who need to reverse-engineer the 'source of truth' within undocumented or legacy codebases. By leveraging advanced symbol clustering and cross-cutting discovery, it identifies decision logic, constraints, and domain behavior that are often buried in implementation details. The skill produces a structured rule catalog that distinguishes intentional business logic from technical infrastructure, making it an essential tool for system audits, codebase onboarding, and preparation for major refactors or rewrites.

Características Principales

01Automated symbol clustering using cartog MCP or deep Grep/Glob analysis

02Cross-cutting detection of rules in middleware, database constraints, and environment configs

03Structured rule catalogs with type identification, confidence scores, and source tracking

04Layered analysis that isolates core logic from infrastructure and framework concerns

05Interactive checkpointing to verify discovery scope before deep-dive analysis

060 GitHub stars

Casos de Uso

01Auditing actual system behavior to verify compliance against intended business requirements

02Onboarding new developers to a complex codebase by providing a domain-specific logic index

03Reverse-engineering undocumented legacy business logic for a system rewrite or migration

Características Principales

01Automated symbol clustering using cartog MCP or deep Grep/Glob analysis

02Cross-cutting detection of rules in middleware, database constraints, and environment configs

03Structured rule catalogs with type identification, confidence scores, and source tracking

04Layered analysis that isolates core logic from infrastructure and framework concerns

05Interactive checkpointing to verify discovery scope before deep-dive analysis

060 GitHub stars

Casos de Uso

01Auditing actual system behavior to verify compliance against intended business requirements

02Onboarding new developers to a complex codebase by providing a domain-specific logic index

03Reverse-engineering undocumented legacy business logic for a system rewrite or migration