ai-assist

Analyze a codebase with a static analyzer and deploy an interactive architecture viewer.

1|Updated Jan 31, 2026
One-click install
npx skills add https://github.com/sirfifer/solution-explorer --skill ai-assist
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: ai-assist
Source: https://github.com/sirfifer/solution-explorer/tree/main/.claude/skills/ai-assist
Command: npx skills add https://github.com/sirfifer/solution-explorer --skill ai-assist

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires python3, npm, npx, git, gh, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill automates the process of analyzing a codebase, enriching it with AI-generated descriptions and annotations, and deploying an interactive architecture viewer.

Core Features & Use Cases

  • Codebase Analysis: Runs a static analyzer to understand code structure, components, and relationships.
  • AI Enhancement: Uses a multi-phase AI pipeline (Digest, Partition, Enhance, Assemble) to add rich metadata, descriptions, and architectural context.
  • Interactive Visualization: Deploys a web-based viewer for exploring the enhanced architecture.
  • Use Case: Improve understanding and documentation of a complex legacy system by generating detailed architectural diagrams and component descriptions automatically.

Quick Start

Run the ai-assist skill to analyze and enhance the codebase located at /path/to/your/codebase.

Frequently Asked Questions about ai-assist

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

FAQPage Schema
How do I generate architecture visualizations for a legacy codebase?▼

You can automate codebase documentation by running a static analyzer to map components, processing results through a multi-phase AI pipeline to add annotations, and deploying an interactive visualization viewer.

How does AI enhancement work for codebase architecture manifests?▼

AI enhancement processes static analyzer output through a multi-phase DPEA pipeline that digests, partitions, enhances, and assembles codebase manifests with rich metadata and architectural descriptions.

Do I need git and npm to run codebase analysis and visualization?▼

Yes, you need python3, npm, npx, git, and gh installed to execute static codebase analysis, run the AI enhancement pipeline, and deploy the interactive architecture visualization viewer.

Can I incrementally update architecture documentation without re-analyzing the whole codebase?▼

Yes, you can perform incremental updates to architecture manifests, allowing you to refresh AI-generated descriptions and visualization data without re-running the full static analyzer on the entire codebase.

What is the best way to validate AI-generated codebase annotations?▼

The best way to validate AI-generated codebase annotations is to use the system's detailed validation features, which verify the accuracy of metadata and architectural context produced by the DPEA pipeline.