analyze

Analyze repository codebases and return ranked findings with confidence levels.

Updated Jul 2, 2026
One-click install
npx skills add https://github.com/JaCha00/nais2-integration-complete --skill analyze-jacha00
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: analyze
Source: https://github.com/JaCha00/nais2-integration-complete/tree/main/.codex/skills/analyze
Command: npx skills add https://github.com/JaCha00/nais2-integration-complete --skill analyze-jacha00

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill provides a comprehensive, read-only analysis of a repository, delivering a ranked synthesis with explicit confidence, concrete file references, and clear evidence-vs-inference boundaries.

Core Features & Use Cases

  • Deep Repository Analysis: Analyze codebases for architecture, behavior, causality, impact, or tradeoffs.
  • Ranked Synthesis: Present a synthesis of findings with explicit confidence levels and evidence.
  • Use Case: When a user needs to understand the underlying reasons for a particular behavior or issue in a codebase before proposing changes.

Quick Start

Use the analyze skill to investigate why a specific workflow behaves a certain way in the repository.

Frequently Asked Questions about analyze

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I investigate why a specific workflow behaves a certain way in a codebase?

You can conduct a read-only deep repository analysis to trace behavior across file boundaries. This delivers a ranked synthesis with concrete file references, helping you understand the underlying reasons for specific codebase behaviors before proposing changes.

What is the best way to analyze repository architecture without modifying the code?

A read-only repository analysis examines architecture safely by tracing behavior across boundaries. It returns a ranked synthesis that explicitly separates concrete evidence from inferred conclusions, ensuring you understand structural tradeoffs without modifying the codebase.

Can I trace behavior across file boundaries to understand causality and impact?

Yes, tracing behavior across boundaries requires reading multiple files during a codebase investigation. This process evaluates architecture, causality, and impact, returning findings ranked by explicit confidence levels and backed by concrete evidence.

Does deep codebase investigation distinguish between actual evidence and inferred conclusions?

Yes, deep codebase investigation distinguishes evidence from inference by setting clear evidence-vs-inference boundaries. The resulting synthesis presents concrete file references alongside explicit confidence levels for every conclusion drawn about repository behavior.

When do I need a ranked synthesis with explicit confidence for repository analysis?

You need a ranked synthesis with explicit confidence when you must understand codebase behavior or architecture before proposing changes. It provides concrete file references and evidence-vs-inference boundaries to ensure safe, well-informed repository modifications.