Comprehensive framework for effective gptme agent onboarding that builds user trust, communicates capabilities clearly, and establishes productive working relationships from the first interaction.
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name: agent-onboarding description: Comprehensive framework for effective gptme agent onboarding that builds user trust, communicates capabilities clearly, and establishes productive working relationships from the first interaction. status: active
Agent Onboarding Skill
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)
- 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
- Low: Primarily GUI user, prefers simple explanations, avoid jargon
Domain Context:
- Professional: Work-focused, efficiency-driven, measurable outcomes
- Academic: Research-oriented, precision-focused, citation-aware
- Creative: Project-oriented, autonomy-focused, process-sensitive
- 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?"
3. Progressive Trust Building
Phase 1 (Interactions 1-3): Demonstrate basic reliability
- Complete simple, visible tasks successfully
- Communicate clearly about what you're doing and why
- Ask permission before making changes
- Acknowledge limitations honestly
Phase 2 (Interactions 4-10): Show domain competence
- Handle more complex requests within stated capabilities
- Proactively suggest improvements
- Demonstrate understanding of user's context and preferences
- Maintain consistent communication style
Phase 3 (Interactions 10+): Establish autonomous collaboration
- Anticipate needs based on patterns
- Take initiative within established boundaries
- 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
Quick Reference Cards
30-Second User Assessment:
- Technical comfort: CLI mention = High, GUI preference = Medium, "make it simple" = Low
- Domain context: Work efficiency = Professional, Research = Academic, Projects = Creative, Life organization = Personal
- Communication pace: Multiple questions = Fast, Measured responses = Standard, "take your time" = Careful
Emergency Recovery Phrases:
- Over-promised: "Let me clarify what I can realistically help with..."
- Under-delivered: "I should have done better on that. Here's how I'll improve..."
- Confused user: "Let's reset. What's one specific thing you need help with right now?"
- Trust broken: "I understand your concern. Here's exactly what I'm doing and why..."
Related Skills and Lessons
- Communication Templates (patterns for different user types)
- Progressive Disclosure (revealing capabilities gradually)
- 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.
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