How does this improve the coding process in Claude Code?

By loading all context upfront, Claude understands the full requirements, edge cases, and architecture, preventing common mistakes caused by missing information.

Does the analyzed context persist during the session?

Yes, once analyzed, the feature context remains in Claude's memory for the duration of the conversation to guide implementation and validation.

Can I use this for existing features or only new ones?

It can be used for any feature directory that follows the structured documentation pattern, making it ideal for both new builds and feature updates.

What documentation files does the Feature Analyzer look for?

It specifically scans for core artifacts like spec.md, ux.md, plan.md, and tasks.md, as well as data-model.md and API contracts.

What happens if a required specification file is missing?

The skill includes a scanner that will alert you to missing core documents, ensuring you have the necessary information before starting implementation.

Feature Context Analyzer

Name: Feature Context Analyzer
Author: petbrains

bypetbrains

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Productividad y Flujo de Trabajo

Automates the scanning and ingestion of feature documentation to build a comprehensive mental model for development.

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The Feature Analyzer is a specialized skill for Claude Code that streamlines the preparation phase of development by programmatically scanning and loading essential feature artifacts. It ingests specifications, UX flows, architectural plans, and task lists to construct a deep understanding of requirements, data models, and technical constraints. By ensuring Claude has a complete mental model of the feature before implementation begins, this skill minimizes errors, ensures requirement traceability, and prepares the environment for high-accuracy TDD and coding tasks.

Características Principales

Comprehensive requirement-to-component mapping
Ingestion of data models, API contracts, and technical research
Context preparation for downstream TDD cycles and task execution
Priority-based loading of specs, UX flows, and architecture plans
Automated artifact discovery and prerequisite validation
3 GitHub stars

Casos de Uso

Building a mental model of complex requirements for architecture queries
Loading full project context before starting a new feature implementation
Analyzing feature completeness and identifying missing documentation

Acerca de

Características Principales

Comprehensive requirement-to-component mapping
Ingestion of data models, API contracts, and technical research
Context preparation for downstream TDD cycles and task execution
Priority-based loading of specs, UX flows, and architecture plans
Automated artifact discovery and prerequisite validation
3 GitHub stars

Casos de Uso

Building a mental model of complex requirements for architecture queries
Loading full project context before starting a new feature implementation
Analyzing feature completeness and identifying missing documentation