feat: Add universal preference discovery system to improve onboarding UX

[blockbtheriault]

🎯 Feature Request: Universal Preference Discovery System

Problem Statement

Current Goose onboarding creates significant friction for new users, as documented in Issue #2329. Users report spending 45+ minutes trying to configure Goose, with many abandoning setup entirely. There's no systematic way to capture user preferences or generate personalized .goosehints files.

Proposed Solution

Integrate the Goose Hints Builder - a production-ready universal preference discovery system that generates personalized .goosehints files through an intuitive wizard interface.

Repository: https://github.com/blockbtheriault/goose-hints-builder

Key Features

• ✅ Universal compatibility - Works across Windows, macOS, Linux without hardcoded assumptions
• ✅ Two editions - Simple (5 categories) and Comprehensive (13 categories)
• ✅ Cross-platform tested - Validated on all major platforms
• ✅ Memory integration - Direct compatibility with Goose memory system
• ✅ Team sharing - Generate standardized preference templates
• ✅ Production ready - Complete error handling, validation, documentation

Alignment with Goose Priorities

• Issue docs: Improve Onboarding experience #2329 - Directly addresses P1 onboarding improvement priority
• Issue Better semantic reporting of what goose is doing #3577 - Provides semantic reporting of user preferences
• PR feat: openrouter out of the box experience for goose installations #3507 - Complements OpenRouter onboarding with preference discovery
• Community growth - Enables shareable team configurations

Technical Implementation Ready

• Help menu integration - Complete UI specifications and React component mockups provided
• CLI integration - goose configure preferences command specifications ready
• Memory system - Tested and working with existing Goose memory infrastructure
• Documentation - Complete user guides, technical specs, and integration guides

Expected Impact

• Reduce onboarding time from 45+ minutes to 5-10 minutes
• Eliminate setup abandonment by providing guided preference discovery
• Improve user retention through personalized first-time experience
• Enable team productivity with standardized organizational preferences

Implementation Approach

1. Phase 1: Integrate preference discovery wizard into Goose Desktop settings
2. Phase 2: Add CLI command support for automated workflows
3. Phase 3: Enable team template sharing and marketplace features

Visual Mockups & Specifications

Complete UI integration specifications available in repository:

• Help menu integration mockups
• Step-by-step wizard interface designs
• Progress tracking and cloud storage integration
• Team template management interface

Request for Team Review

This is a complete, tested solution ready for integration discussion. The system addresses one of Goose's highest-priority UX challenges with a production-ready implementation.

Ready for immediate collaboration on:

• Technical integration planning
• UX design refinement
• Beta testing coordination
• Community rollout strategy

Additional Context

• MIT License - Open source compatible
• GitHub Actions - CI/CD pipeline operational
• Issue templates - Community contribution ready
• Cross-platform validation - Universal compatibility confirmed

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Repository: https://github.com/blockbtheriault/goose-hints-builder
Status: Production-ready, awaiting integration discussion

[michaelneale]

I'm not sure what this is? a separate install utility type thing people can use?

[blockbtheriault]

I was thinking more like a native Goose feature proposal - rather than a separate install utility - integrated directly into Goose's Help menu as a guided walkthrough to create a starter hints file. Took me awhile to get that and I thought it could be useful to others. Also the linked repository has a working version if you’d want to try it :)

How It Works

1. Accessible via Help > Goose Hints Builder in the Goose interface
2. Interactive Setup: Users answer 5-13 questions about their preferences (coding languages, output formats, communication style, etc.)
3. Automatic Memory Storage: Responses are saved to Goose's memory system as personalized hints
4. Immediate Activation: Preferences take effect immediately in all future conversations

[DOsinga]

the linked repository is in python though while goose is in rust, so that seems hard to integrate. I'll close this for now