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titan-recon

Maps a codebase's dependency graph to reveal hotspots, domains, and prioritized cleanup tasks.

86|20|Updated Feb 21, 2026
Search Tags:#automation#domain#dependency-graph#architecture-document#codegraph#titan#work-batches
One-click install
npx skills add https://github.com/optave/ops-codegraph-tool --skill titan-recon
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: titan-recon
Source: https://github.com/optave/ops-codegraph-tool/tree/main/.claude/skills/titan-recon
Command: npx skills add https://github.com/optave/ops-codegraph-tool --skill titan-recon

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Titan RECON maps a codebase's dependency graph to reveal hotspots, name logical domains, and produce a prioritized cleanup backlog to guide autonomous phases.

Core Features & Use Cases

  • Build a comprehensive function-level dependency graph and surface structural hotspots for optimization.
  • Name logical domains and generate a global architecture document to guide refactors and team alignment.
  • Propose work batches (up to 5 files each) and initialize a ranked cleanup queue for downstream Titan phases.

Quick Start

Run Titan Recon on the target repository and generate an initial titan-state.json in .codegraph/titan

Frequently Asked Questions about titan-recon

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

FAQPage Schema
Does dependency graph analysis work for planning automated refactoring batches?▼

Dependency graph analysis works for planning automated refactoring by mapping function relationships into manageable work batches. Titan RECON supports this by producing a ranked cleanup queue tailored for downstream Titan phases.

How do I map a codebase dependency graph to find structural hotspots?▼

Mapping a codebase dependency graph builds a function-level view to reveal structural hotspots and domains. Titan RECON analyzes the repository to surface optimization targets and name logical boundaries for team alignment.

What is the best way to generate an architecture document from source code dependencies?▼

Generating an architecture document from dependencies extracts logical domains to produce a global structural overview. Titan RECON outputs a GLOBAL_ARCH.md file to guide refactoring efforts and align development teams.

How do I create a prioritized cleanup backlog for a large codebase?▼

Creating a cleanup backlog for a large codebase prioritizes refactoring tasks into ranked work batches. Titan RECON proposes batches of up to 5 files each, initializing a queue for downstream automated phases.

Can I automate codebase cleanup planning for medium-to-large repositories?▼

Automating cleanup planning for medium-to-large repositories generates deterministic work batches and state artifacts. Titan RECON initializes a titan-state.json file in the .codegraph/titan directory to drive autonomous execution.

Does dependency graph analysis work for planning automated refactoring batches?▼

Dependency graph analysis works for planning automated refactoring by mapping function relationships into manageable work batches. Titan RECON supports this by producing a ranked cleanup queue tailored for downstream Titan phases.

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