dojo-stage

Manage Codojo learning protocol state and routing across AI sessions.

52|3|Updated Jun 27, 2026
One-click install
npx skills add https://github.com/ttguy0707/codojo --skill dojo-stage
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: dojo-stage
Source: https://github.com/ttguy0707/codojo/tree/main/skills/dojo-stage
Command: npx skills add https://github.com/ttguy0707/codojo --skill dojo-stage

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill eliminates the confusion of tracking progress across multiple AI sessions by automatically detecting your current learning stage and routing you to the correct task.

Core Features & Use Cases

  • Automated Progress Tracking: Monitors the .codojo/ directory to determine if you are in the assessment, planning, teaching, or hacking phase.
  • Context Recovery: Seamlessly resumes your learning journey after an interruption by identifying the last completed milestone.
  • Use Case: When you return to a project after a week, simply trigger this skill to receive a status report and a direct prompt to resume exactly where you left off.

Quick Start

Trigger the dojo-stage skill by asking the agent to help you learn this project or check your current progress.

Frequently Asked Questions about dojo-stage

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

FAQPage Schema
How do I track my learning progress across multiple AI sessions?

Tracking learning progress across multiple AI sessions requires a state machine that evaluates metadata files in the .codojo directory to determine your current educational phase and resume exactly where you left off.

How does automated phase routing work for project onboarding?

Automated phase routing works by detecting project-specific completion markers to coordinate transitions between assessment, planning, teaching, and project modification stages without manual configuration.

How do I resume a learning journey after an interruption?

Resuming a learning journey after an interruption involves triggering the skill to identify the last completed milestone and generate a status report with a direct prompt to continue.

Do I need a specific directory structure to manage learning workflow state?

Managing learning workflow state requires a .codojo directory containing project-specific metadata files that the state machine evaluates to detect your current phase and route transitions correctly.

What is the best way to route transitions between teaching and project modification stages?

Routing transitions between teaching and project modification stages is best handled by evaluating predefined completion markers within the .codojo directory to automatically trigger the next educational phase.

Why does my learning protocol context drop when starting a new AI session?

Learning protocol context drops in new AI sessions because the underlying state machine lacks automated progress tracking; triggering the skill evaluates your .codojo metadata to recover and restore the exact context.