rp-why

name	rp-why
description	Gas Town × DOK Framework - A two-dimensional model for analyzing AI collaboration maturity and cognitive complexity to reveal growth opportunities.
author	dakotafabro
version	3.0
tags	["reflection","growth","ai-collaboration","self-assessment","productivity","learning"]

rp-why: Gas Town × DOK Framework

Overview

The rp-why skill is a self-reflection framework that helps AI practitioners measure and improve their AI collaboration practice. It combines two powerful dimensions:

• Horizontal Axis: Gas Town Stages — Measures AI tool adoption maturity from basic chatbots to multi-agent orchestration
• Vertical Axis: DOK Levels — Measures the cognitive complexity of prompts from simple recall to extended thinking

The intersection of these dimensions reveals growth opportunities and helps users maximize the value they extract from their AI tools.

---

How to Use This Skill

Installation

Install the skill using the skills CLI:

npx skills add https://github.com/block/agent-skills --skill rp-why

Make sure you have the built-in skills extension enabled in your agent (Goose, Claude Desktop, etc.).

Using Slash Commands

Once the skill is loaded, you can use slash commands directly in your conversation:

You: /rp-why current

Goose will analyze your current session and provide:

• Your Gas Town stage assessment
• DOK distribution breakdown
• Quadrant position
• Growth nudges

Available Commands

Command	What It Does
/rp-why current	Analyze the current session
/rp-why init	Generate a baseline from your history
/rp-why compare	Compare current session to baseline

Alternative: Natural Language

You don't have to use slash commands. You can also just ask naturally:

You: Analyze my AI collaboration patterns using the Gas Town DOK framework
You: What's my DOK distribution for this session?
You: How does this session compare to my baseline?

The skill will recognize these requests and provide the same analysis.

When to Use

• End of session: Run /rp-why current to reflect on your work
• Weekly: Run /rp-why compare to track progress
• First time: Run /rp-why init to establish your baseline

---

Problem Statement

Many AI practitioners face a hidden inefficiency: a mismatch between tool sophistication and task cognitive complexity.

Anti-Pattern	Impact
Using powerful autonomous agents for simple "what is X?" queries	Unrealized potential
Asking deep strategic questions through basic chatbot interfaces	Bottlenecked thinking
No visibility into personal AI usage patterns	Stagnant growth
No framework for intentional growth in AI collaboration skills	Missed opportunities

Without measurement, there's no improvement. Users need a mirror to see their AI collaboration patterns clearly.

---

The Framework

Yegge's 8 Gas Town Stages (AI Tool Adoption)

From Steve Yegge's "Welcome to Gas Town" (January 2026):

Stage	Name	Description
8	Full Gas Town	Complete AI-native development ecosystem
7	Agentic Workflows	Automated pipelines with agent coordination
6	Multi-Agent	Orchestrating multiple specialized agents
5	CLI Single Agent, YOLO	Terminal-based autonomous agent (e.g., Goose)
4	Chat IDE	Integrated chat in development environment
3	Copilot	Using AI code completion, inline suggestions
2	Curious	Experimenting with basic chatbots occasionally
1	Observer	Watching and evaluating AI tools, not yet actively using

Webb's DOK Levels (Cognitive Complexity)

From Norman Webb's Depth of Knowledge framework (1997):

Level	Name	Description	Prompt Indicators
4	Extended Thinking	Complex investigation, multiple sessions	"Research and synthesize...", "Create a framework...", "Investigate over time..."
3	Strategic Thinking	Reasoning, planning, analysis, synthesis	"Design...", "Analyze...", "What if...", "Develop a strategy..."
2	Application	Apply concepts, make decisions, compare	"How would you...", "Compare...", "Explain why..."
1	Recall	Facts, definitions, simple procedures	"What is...", "List...", "Define..."

Integration Matrix (Stage × DOK)

The intersection creates six distinct zones:

              DOK 1        DOK 2         DOK 3          DOK 4
            (Recall)   (Application) (Strategic)   (Extended)
           ┌──────────┬──────────────┬────────────┬────────────┐
Stage 6-8  │   Over-  │    Over-     │ Underutil- │  Frontier  │
(Multi/    │  powered │   powered    │   izing    │            │
 Agentic)  │          │              │            │            │
           ├──────────┼──────────────┼────────────┼────────────┤
Stage 5    │   Over-  │  Underutil-  │  Expected  │  Growing   │
(CLI YOLO) │  powered │    izing     │            │            │
           ├──────────┼──────────────┼────────────┼────────────┤
Stage 3-4  │   Over-  │   Expected   │  Growing   │  Frontier  │
(Copilot/  │  powered │              │            │            │
 Chat IDE) │          │              │            │            │
           ├──────────┼──────────────┼────────────┼────────────┤
Stage 1-2  │ Expected │   Growing    │  Thinking  │  Thinking  │
(Observer/ │          │              │   Ahead    │   Ahead    │
 Curious)  │          │              │            │            │
           └──────────┴──────────────┴────────────┴────────────┘

Zone Definitions:

Zone	Description	Action
Frontier	Pushing boundaries of both tool and cognition	Celebrate & Document
Thinking Ahead	High cognitive work with basic tools	Upgrade tools
Growing	Stretching into higher complexity, positive trajectory	Encourage
Expected	Appropriate match of tool sophistication to task complexity	Maintain
Underutilizing	Sophisticated tools for simpler tasks	Increase DOK
Overpowered	Tools exceed task needs—opportunity to level up your questions	Realign

---

Commands

/rp-why current

Analyze the current session's Gas Town stage and DOK distribution.

Output includes:

• Stage assessment with confidence level
• DOK distribution breakdown with percentages
• Quadrant position visualization
• Contextual growth nudges
• Reflection prompt

/rp-why init

Generate a baseline from your conversation history (analyzes available sessions).

Output includes:

• Historical analysis period and session count
• Baseline DOK distribution
• Typical Gas Town stage
• Growth targets
• Baseline saved to ~/.config/goose/rp-why-baseline.json

/rp-why compare

Compare current session against your established baseline.

Output includes:

• Side-by-side DOK comparison (baseline vs current)
• Quadrant movement visualization
• Progress toward growth targets
• Trajectory analysis

---

Sample Output

╔══════════════════════════════════════════════════════════════════╗
║                    rp-why: CURRENT SESSION                       ║
╚══════════════════════════════════════════════════════════════════╝

GAS TOWN STAGE: 5 (CLI Single Agent, YOLO)

DOK DISTRIBUTION
────────────────────────────────────────────────────────────────────
DOK 1 (Recall):      ████░░░░░░░░░░░░░░░░  17%
DOK 2 (Application): ████████████░░░░░░░░  52%
DOK 3 (Strategic):   ██████░░░░░░░░░░░░░░  26%
DOK 4 (Extended):    █░░░░░░░░░░░░░░░░░░░   5%

QUADRANT: Underutilizing
────────────────────────────────────────────────────────────────────
You're using powerful autonomous tools—there's an opportunity to
match your questions to that power.

GROWTH NUDGES
────────────────────────────────────────────────────────────────────
1. Shift 2-3 DOK 2 prompts to DOK 3 by adding "analyze trade-offs"
2. Before simple queries, ask: "Can I make this more strategic?"
3. Try one DOK 4 extended investigation this week

🪞 REFLECTION
────────────────────────────────────────────────────────────────────
What complex challenge could benefit from your agent's full
capabilities today?

---

Target User Profiles

Profile	Typical Stage	DOK Distribution	Characteristics
Traditional	1-2	DOK1: 60%, DOK2: 30%, DOK3: 10%	Minimal AI use
Adopter	3-4	DOK1: 40%, DOK2: 40%, DOK3: 15%, DOK4: 5%	Growing comfort
Practitioner	5	DOK1: 25%, DOK2: 45%, DOK3: 25%, DOK4: 5%	Autonomous agents
Advanced	5-6	DOK1: 15%, DOK2: 35%, DOK3: 35%, DOK4: 15%	Strategic use
Frontier	7-8	DOK1: 10%, DOK2: 25%, DOK3: 40%, DOK4: 25%	Agentic workflows

---

Growth Nudge Reference

Frontier (High Stage, High DOK)

• "You're pushing boundaries—document what you learn"
• "Share patterns with others; teach what works"
• "Explore the edges: what's not yet possible?"

Thinking Ahead (Low Stage, High DOK)

• "Your thinking exceeds your tools—time to upgrade!"
• "Explore CLI agents or IDE integration"
• "Your DOK is strong; let better tools amplify it"

Underutilizing (High Stage, Lower DOK)

• "Powerful tools deserve powerful questions"
• "Before each prompt, ask: Can this be more strategic?"
• "Batch simple queries; save the agent for complex work"

Learning Zone (Low Stage, Low DOK)

• "This is a natural starting point—focus on learning the tools"
• "Try one new AI capability each session"
• "Don't worry about DOK yet—get comfortable first"

Overpowered (High Stage, Low DOK)

• "Your tools exceed your task needs—opportunity to level up your questions"
• "Consider: Is this query worth an autonomous agent?"
• "Batch simple lookups; reserve agent for strategic work"

---

Upgrading Your Prompts

DOK Level	Prompt Pattern	Example
1 → 2	Add "how" or "why"	"What is a mutex?" → "How would I use a mutex here?"
2 → 3	Add "trade-offs" or "design"	"How do I implement caching?" → "Design a caching strategy considering our constraints"
3 → 4	Extend across sessions	"Analyze this architecture" → "Research caching patterns over multiple sessions and synthesize recommendations"

---

Attribution

• Gas Town Stages: Steve Yegge, "Welcome to Gas Town" (January 2026) https://steve-yegge.medium.com/welcome-to-gas-town-4f25ee16dd04

• Depth of Knowledge (DOK): Norman Webb (1997) Webb, N. L. (1997). Criteria for alignment of expectations and assessments in mathematics and science education. Council of Chief State School Officers.

---

Version History

Version	Date	Changes
3.0	2026-02	Quadrant visualization, growth nudges, reflection prompts, updated terminology
2.x	2026-01	Integration matrix, target profiles, baseline comparison
1.x	2025-12	Initial Gas Town stages, basic DOK tracking