architecture-deepener

Encontra oportunidades de "deepening" no codebase — refactors que transformam modulos shallow (interface complexa, implementacao simples) em deep (interface simples, implementacao rica). Foco em testabilidade e AI-navigability. Use quando usuario quiser melhorar arquitetura, encontrar oportunidades de refactor, consolidar modulos acoplados, ou preparar codebase para trabalho de agente. Trigger em: "deepening", "deep module", "shallow module", "refactor architecture", "improve architecture", "consolidate modules", "agent-friendly codebase", "AI-navigable", "module depth".

What does this entry provide?

architecture-deepener is an agent skill entry in ChatHome Skills, sourced from GitHub Skill Search and scored 58/100. # Architecture Deepener — Refactors que Importam Identificar friccao arquitetural e propor **deepening opportunities** — refactors que transformam modulos shall. As an agent skill, it packages a reusable instruction set that AI coding agents such as Codex and Claude Code can load to perform this task without hand-written glue code. ChatHome Skills discovered this entry through its daily ingest of official registries and GitHub discovery queries, and re-verifies repository facts, freshness signals, and install metadata on every run. The quality score weighs official-registry presence, a working install command, license clarity, GitHub star trajectory, and repository freshness — the full formula is on the Sources page. The install command above is ready to copy. Review the last-pushed date and repository status before adding architecture-deepener to a production agent workflow; the snapshot facts below are point-in-time values from the most recent ingest.

Snapshot facts

Source: GitHub Skill Search
Quality: 58/100
Install method: codex
Repo: felvieira/claude-skills-fv
Repo updated: Oct 23, 2026

Install command

codex skill install felvieira/claude-skills-fv

Install method: codex

Review the upstream source before running this command.

GitHub project

Quality

Repo stars

Repo updated

Unknown

How is this score calculated?

Weighted across six dimensions, scored 0-100.
Provenance (25): listed in an official or curated registry.
Installability (25): a runnable install command beats a declared transport, which beats a source checkout.
Maintenance (20): recency of the last push; archived entries score zero here.
Adoption (20): repository stars on a log curve.

Security signals

Scan coverage: Install metadata and the indexed document body.

Automated signals from install metadata and a bounded skill body — not a full code security audit and not a recursive source or dependency review.

Discovery note

# Architecture Deepener — Refactors que Importam Identificar friccao arquitetural e propor **deepening opportunities** — refactors que transformam modulos shallow em deep. Objetivo

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