Can it help with identifying code smells?

Yes, the skill includes red flag detection and quality assessment capabilities to surface anti-patterns and maintainability issues during the analysis process.

Does it support long-term project maintenance?

Yes, Phase 8 of the skill specifically handles documentation health, fixing broken links, updating navigation indexes, and identifying documentation drift.

How does this differ from standard documentation generators?

Unlike tools that only parse docstrings, this skill combines mechanical extraction with Claude's semantic reasoning to explain design intent, business purpose, and cross-file dependencies.

What is the 'Absolute Source of Truth' principle?

It is a mandatory rule where all generated documentation must be derived and verified directly from the current source code, treating existing comments or docs as unverified until proven.

What are the prerequisites for using this skill?

The project requires Python 3.13 or higher and an initialized analysis_progress.json file in the root directory to track the status of different codebase phases.

Deep Dive Codebase Analysis

Name: Deep Dive Codebase Analysis
Author: acaprino

byacaprino

Learning & Documentation

Performs systematic, AI-powered codebase analysis to generate high-fidelity documentation that captures both mechanical structure and semantic intent.

About

The Deep Dive Analysis skill bridges the gap between raw code parsing and human-centric understanding by combining automated structure extraction with Claude's semantic reasoning. It moves beyond simple structural summaries to explain the 'why' behind design decisions and the 'how' of system integration, all while enforcing a strict 'source of truth' policy. By verifying documentation against actual source code and removing historical noise, it ensures that technical guides, architecture maps, and onboarding materials remain accurate, present-tense, and irrefutably grounded in the current implementation.

Key Features

Multi-layer verification (Tool/Human/Runtime) to ensure documentation matches source code.
Phase-based analysis progress tracking for large-scale codebase onboarding.
0 GitHub stars
Automated documentation maintenance including link validation and navigation index updates.
Semantic pattern recognition to identify architectural design and potential anti-patterns.
Mechanical structure extraction for classes, functions, and internal/external dependencies.

Use Cases

Performing deep architectural reviews to identify systemic red flags and side effects.
Rapidly onboarding to large or unfamiliar codebases by generating semantic maps.
Creating and maintaining technical documentation that stays in sync with implementation changes.

About

Key Features

Multi-layer verification (Tool/Human/Runtime) to ensure documentation matches source code.
Phase-based analysis progress tracking for large-scale codebase onboarding.
0 GitHub stars
Automated documentation maintenance including link validation and navigation index updates.
Semantic pattern recognition to identify architectural design and potential anti-patterns.
Mechanical structure extraction for classes, functions, and internal/external dependencies.

Use Cases

Performing deep architectural reviews to identify systemic red flags and side effects.
Rapidly onboarding to large or unfamiliar codebases by generating semantic maps.
Creating and maintaining technical documentation that stays in sync with implementation changes.