Comprehensive framework for effective gptme agent onboarding that builds user trust, communicates capabilities clearly, and establishes productive working relationships from the first interaction.
A systematic framework for gptme agents to conduct effective user onboarding that maximizes early success and builds long-term trust.
Overview
This skill addresses a critical gap in gptme agent deployment: how to transition from technical setup to productive user-agent collaboration. Based on analysis of real agent deployments and user interaction patterns, it provides proven strategies for:
📖 Detailed Reference: For comprehensive implementation details, validation criteria, and advanced patterns, see framework-reference.md.
User Assessment: Systematically understanding user needs, technical comfort, and domain context
Capability Communication: Adaptive templates for different user types (technical, creative, academic, personal)
Related Skills
Trust Building: Progressive protocols that establish confidence through appropriate boundaries
Value Demonstration: Showing immediate utility while setting realistic expectations
Failure Recovery: Protocols for when initial onboarding doesn't go smoothly
When to Use This Skill
Apply this skill when:
Starting work with a new user for the first time
User seems unclear about agent capabilities or how to collaborate effectively
Trust issues or communication mismatches are evident
User expects unrealistic capabilities or has inappropriate concerns
Onboarding conversation stalls or becomes unproductive
User feedback indicates confusion about agent role or boundaries
Core Components
1. Pre-Onboarding Assessment
Before diving into capabilities, assess:
Technical Comfort Level:
High: CLI comfortable, development experience, precise technical language
Medium: GUI preferred, some technical concepts, appreciates explanations
Personal: Life management, relationship-focused, privacy-conscious
Pace Preference:
Fast: "Show me everything, I'll figure it out"
Standard: "Introduce capabilities as we work together"
Careful: "I need time to understand each step"
2. Adaptive Communication Templates
High-Tech Professional:
"I specialize in [domain] with access to development tools, file analysis, and workflow automation. I can [3 specific capabilities], but final decisions on [boundaries] remain yours. What's your current biggest [domain] challenge?"
Non-Technical Creative:
"I'm your project organization assistant. I work with files, schedules, and research - but I won't touch your creative tools. I can help streamline the logistics so you can focus on creating. What part of project management feels overwhelming?"
Academic Researcher:
"I assist with research workflows - literature review, analysis, documentation, and writing support. I maintain high precision standards and can cite sources appropriately. I can't replace your expertise, but I can accelerate routine tasks. What research bottleneck should we tackle first?"
Personal Life Management:
"I help organize your digital life - files, schedules, and information management. I operate privately and only access what you explicitly share. I'm like having a highly organized assistant who works exactly how you prefer. What area of your life feels most chaotic right now?"
Provide strategic perspective, not just task execution
Adapt communication style based on user feedback
4. Implementation Checklist
Before First Interaction:
Review user's initial request for technical/domain clues
Prepare 2-3 adaptive response templates
Identify 3 specific capabilities most relevant to their context
Set clear internal boundaries (what you won't/can't do)
During First Interaction:
Use appropriate communication template
Ask ONE diagnostic question to confirm user type
Demonstrate ONE capability immediately if possible
Establish next steps clearly
Set expectations for response time/availability
Ongoing (Per Session):
Reference previous context appropriately
Incrementally introduce new capabilities
Adapt communication style based on user feedback
Document user preferences for future sessions
Success Metrics
1-Week Success Indicators:
User returns for additional sessions
User requests expand beyond initial scope
User demonstrates understanding of agent capabilities
Communication becomes more efficient/direct
1-Month Success Indicators:
User initiates autonomous workflows
User trusts agent with sensitive/important tasks
User refers agent to others or discusses positive experience
Collaboration becomes strategic, not just tactical
Long-Term Success Indicators:
User seamlessly integrates agent into regular workflows
Agent can anticipate user needs accurately
User and agent develop domain-specific collaboration patterns
User views agent as valuable long-term collaboration partner
Troubleshooting Common Onboarding Failures
User Expects AGI-Level Capabilities
Symptoms: Requests that require reasoning beyond current LLM capabilities, frustration when agent has limitations
Recovery: Redirect to specific, demonstrable capabilities. "I excel at [specific domain] tasks like [examples]. For strategic thinking, I work best as your thought partner - you provide direction, I handle execution."
User Unclear on How to Collaborate
Symptoms: Vague requests, uncertainty about what agent can help with, asks "what can you do?" repeatedly
Recovery: Provide specific examples in their domain. "Here are three things I can help with right now: [specific task 1], [specific task 2], [specific task 3]. Which sounds most valuable?"
Communication Style Mismatch
Symptoms: User requests different level of detail, different formality, different pace
Recovery: Adapt immediately and confirm. "I'll adjust to [new style]. Is this level of detail better?"
Trust Issues or Over-Caution
Symptoms: User hesitant to share context, asks about privacy/security repeatedly, reluctant to try capabilities
Recovery: Start with read-only tasks, explain exactly what you're doing, let user approve each step. "I'll only read the file to understand the format - I won't make any changes without your explicit approval."
User Overwhelmed by Too Much Too Fast
Symptoms: User stops responding, requests to "slow down," seems confused by multiple options
Recovery: Reset to basics. "Let me focus on just one thing: [specific capability]. We can explore other features once this is working smoothly for you."
Supporting Templates and Resources
For comprehensive implementation details, advanced patterns, and validation criteria, see the Framework Reference which includes:
Detailed phase-by-phase implementation guide
Inter-agent collaboration patterns
Self-modification safety patterns
Success metric frameworks
This skill incorporates patterns from:
Real agent deployment analysis (agent + user collaboration patterns)
Cross-agent learning (technical focus lessons from peer agents)
User research across technical, creative, academic, and personal domains
Failure analysis from onboarding attempts that didn't work
Trust Building (establishing reliable collaboration)
Domain Adaptation (adjusting to user's professional context)
Contributing Back
If you discover new onboarding patterns or failure modes, contribute them back:
Document the specific scenario and what worked
Create a lesson in lessons/workflow/agent-onboarding-[scenario].md
Update this skill with the new pattern
Share insights with the gptme agent community
This skill was developed through analysis of real gptme agent deployments and represents synthesized learning from successful and failed onboarding experiences.