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tune-repo

Build a codified context architecture with routing tables and memory documentation for a repository.

13|3|Updated Mar 2, 2026
Search Tags:#AI onboarding#codebase documentation#agent productivity#agent tuning#context architecture#repository specialization
One-click install
npx skills add https://github.com/phrazzld/agent-skills --skill tune-repo
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: tune-repo
Source: https://github.com/phrazzld/agent-skills/tree/main/core/tune-repo
Command: npx skills add https://github.com/phrazzld/agent-skills --skill tune-repo

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This Skill transforms a generic repository into a finely tuned workspace for AI agents, ensuring they operate with full project awareness and autonomy.

Core Features & Use Cases

  • Context Architecture: Builds a complete agent context including hot-memory constitution, routing tables, and cold-memory subsystem documentation.
  • Agent Specialization: Deeply customizes agents for specific repositories, improving their effectiveness in tasks like building, debugging, and PR workflows.
  • Use Case: When onboarding to a new or complex codebase, use this Skill to establish a robust knowledge base and operational guidelines for your AI coding assistants.

Quick Start

Run the tune-repo skill to audit and update the context architecture for the current repository.

Frequently Asked Questions about tune-repo

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

FAQPage Schema
How do I onboard an AI agent to a complex codebase?▼

Onboard an AI agent to a complex codebase by building a codified context architecture. This establishes hot-memory constitutions and routing tables to ensure the agent operates with full project awareness and autonomy.

What is agent context architecture for repository specialization?▼

Agent context architecture is a structured knowledge framework that specializes AI agents for specific repositories. It builds hot-memory constitutions, routing tables, and cold-memory subsystem documentation to enhance agent effectiveness.

How do I improve AI agent productivity during build and PR workflows?▼

Improve AI agent productivity in build and PR workflows by deeply customizing the agent for your repository. Specializing the agent establishes operational guidelines and a robust knowledge base for autonomous task execution.

When should I build cold-memory subsystem documentation for my codebase?▼

Build cold-memory subsystem documentation when onboarding to a new or complex codebase. This creates a finely tuned workspace that ensures AI coding assistants have the deep context required for effective debugging and building tasks.

Does agent tuning work without adding external dependencies?▼

Agent tuning works without external dependencies by generating internal repository artifacts. The process creates supporting scripts, references, and assets directly within your repo to guide the AI agent's behavior.

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