Can it identify missing information?

Yes, the skill is designed to flag 'Gaps' and 'Unknowns' using specific caveat markers (△) to ensure you know what has not yet been verified.

How does confidence tracking work in this skill?

The skill tracks certainty on a 0-5 scale, where Level 0 is initial evidence gathering and Level 5 is a fully verified conclusion supported by multiple data sources.

When should I use Codebase Recon instead of standard search?

Use this skill when you need to understand 'why' or 'how' a system works as a whole, rather than just finding a specific line of code, especially during architectural planning or refactoring.

What is the Codebase Recon skill?

It is a specialized framework for Claude Code that enables systematic, evidence-driven exploration and mapping of software repositories to provide deep architectural insights.

Codebase Recon

Name: Codebase Recon
Author: outfitter-dev

byoutfitter-dev

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Developer Tools

Analyzes and maps complex codebases using a systematic, evidence-based approach to ensure deep architectural understanding.

About

Codebase Recon is a specialized capability for Claude Code designed to transform how developers explore and understand unfamiliar or complex software systems. Instead of relying on guesswork, this skill implements a rigorous investigation framework that gathers evidence from source code, documentation, test suites, and version history. It utilizes a unique confidence-tracking system (Levels 0-5) to communicate the certainty of its findings, making it an essential tool for onboarding to new projects, conducting technical audits, and identifying architectural patterns before implementing major changes.

Key Features

Multi-source analysis spanning code, documentation, tests, and git history
Evidence-based investigation methodology that prioritizes facts over assumptions
Structured reporting format including findings, patterns, and documented caveats
Dynamic confidence tracking from initial survey (Level 0) to final conclusion (Level 5)
18 GitHub stars
Seamless integration with specialized skills for pattern recognition and root-cause analysis

Use Cases

Onboarding to a new or legacy codebase to map architecture and dependencies
Conducting deep-dive technical research and architectural audits
Extracting and validating recurring design patterns within a repository

About

Key Features

Multi-source analysis spanning code, documentation, tests, and git history
Evidence-based investigation methodology that prioritizes facts over assumptions
Structured reporting format including findings, patterns, and documented caveats
Dynamic confidence tracking from initial survey (Level 0) to final conclusion (Level 5)
18 GitHub stars
Seamless integration with specialized skills for pattern recognition and root-cause analysis

Use Cases

Onboarding to a new or legacy codebase to map architecture and dependencies
Conducting deep-dive technical research and architectural audits
Extracting and validating recurring design patterns within a repository