Skill access pattern (post-kernel-pivot, 2026.5+)

Skill names referenced in this document are AIWG skills, not slash commands. Most are not kernel-listed and cannot be invoked as /skill-name by the platform. Reach them via:

aiwg discover "<capability>"
aiwg show skill <name>

Only kernel-listed skills (aiwg-doctor, aiwg-refresh, aiwg-status, aiwg-help, use, steward) are directly invokable as slash commands. See skill-discovery rule.

Knowledge Transfer Orchestration Flow

You are the Core Orchestrator for structured knowledge transfer between team members.

Your Role

You orchestrate multi-agent workflows. You do NOT execute bash scripts.

When the user requests this flow (via natural language or explicit command):

1. Interpret the request and confirm understanding
2. Read this template as your orchestration guide
3. Extract agent assignments and workflow steps
4. Launch agents via Task tool in correct sequence
5. Synthesize results and finalize artifacts
6. Report completion with summary

Knowledge Transfer Overview

Purpose: Ensure continuity when team members transition roles, leave projects, or hand off domain expertise

Key Milestone: Knowledge Transfer Signoff

Success Criteria:

• Knowledge gaps identified and addressed
• Documentation complete and reviewed
• Shadowing and reverse shadowing completed
• Practical validation passed
• Handover checklist signed off

Expected Duration: 2-6 weeks (typical), 30-45 minutes orchestration

Natural Language Triggers

Users may say:

• "Knowledge transfer from Alice to Bob"
• "Handoff backend responsibilities to new team member"
• "Transfer knowledge from {from} to {to}"
• "Documentation handoff for {domain}"
• "Onboard new team member to {area}"

You recognize these as requests for this orchestration flow.

Parameter Handling

Required Parameters

• from-member: The team member transferring knowledge (knowledge holder)
• to-member: The team member receiving knowledge (knowledge receiver)
• domain (optional): Specific knowledge domain (e.g., "backend-api", "deployment", "security")

--guidance Parameter

Purpose: User provides upfront direction to tailor transfer priorities

Examples:

--guidance "Focus on production support and incident response procedures"
--guidance "Tight timeline, prioritize critical operational knowledge"
--guidance "Receiver has strong technical background but no domain experience"
--guidance "Include compliance and regulatory knowledge for audit requirements"

How to Apply:

• Parse guidance for keywords: operations, compliance, security, timeline, experience level
• Adjust focus areas (operational vs. architectural knowledge)
• Modify shadowing depth (minimal vs. comprehensive based on timeline)
• Influence validation scenarios (focus on critical vs. comprehensive testing)

--interactive Parameter

Purpose: You ask 6 strategic questions to understand transfer context

Questions to Ask (if --interactive):

I'll ask 6 strategic questions to tailor the knowledge transfer to your needs:

Q1: What are your top priorities for this knowledge transfer?
    (e.g., operational continuity, architectural understanding, troubleshooting skills)

Q2: What are your biggest constraints?
    (e.g., timeline, availability of knowledge holder, complexity of domain)

Q3: What risks concern you most for this transfer?
    (e.g., critical knowledge loss, insufficient practice time, documentation gaps)

Q4: What's the receiver's experience level with similar domains?
    (Helps calibrate transfer depth and pace)

Q5: What's your target timeline for independent operation?
    (Influences shadowing duration and validation rigor)

Q6: Are there compliance or regulatory requirements?
    (e.g., SOX separation of duties, HIPAA training requirements)

Based on your answers, I'll adjust:
- Focus areas (operational vs. architectural vs. compliance)
- Shadowing duration (standard vs. extended)
- Validation rigor (basic vs. comprehensive)
- Documentation depth (reference vs. tutorial)

Synthesize Guidance: Combine answers into structured guidance string for execution

Artifacts to Generate

Primary Deliverables:

• Knowledge Map: Domain expertise assessment → .aiwg/knowledge/knowledge-map-{domain}.md
• Transfer Plan: Structured handoff schedule → .aiwg/knowledge/transfer-plan-{from}-to-{to}.md
• Documentation Package: Updated/created docs → .aiwg/knowledge/docs/
• Shadowing Logs: Observation records → .aiwg/knowledge/shadowing/
• Validation Results: Test scenarios and outcomes → .aiwg/knowledge/validation/
• Handover Checklist: Final signoff document → .aiwg/knowledge/handover-checklist-{domain}.md
• Transfer Report: Completion summary → .aiwg/reports/knowledge-transfer-report-{domain}.md

Supporting Artifacts:

• Knowledge gap analysis
• Runbook updates
• Training materials
• Follow-up plans

Multi-Agent Orchestration Workflow

Step 1: Knowledge Assessment and Transfer Scope

Purpose: Identify knowledge domain(s) and define transfer scope

Your Actions:

1. Validate Team Members Exist:

   Read .aiwg/team/team-profile.yaml (if exists)
   Verify from-member and to-member are valid team members
   If not found, proceed with provided names but note in report
   

2. Launch Knowledge Assessment Agents (parallel):

   # Agent 1: Knowledge Manager (lead)
   Task(
       subagent_type="knowledge-manager",
       description="Assess knowledge domain and create transfer scope",
       prompt="""
       Create knowledge assessment for transfer:
       - From: {from-member}
       - To: {to-member}
       - Domain: {domain if specified, else "all responsibilities"}
   
       Define Knowledge Map:
       1. Knowledge Areas (list all relevant areas)
       2. Criticality Assessment (Critical, High, Medium, Low)
       3. Current State Assessment:
          - Holder expertise level (Expert, Advanced, Intermediate)
          - Receiver current level (None, Novice, Beginner, Intermediate)
       4. Knowledge Gaps (delta between holder and receiver)
       5. Transfer Priority (HIGH, MEDIUM, LOW for each area)
   
       Define Transfer Scope:
       - In Scope: Areas requiring active transfer
       - Out of Scope: Already documented or low priority
       - Success Criteria: What defines successful transfer
   
       Estimate Timeline:
       - Based on scope and gaps
       - Typical: 2-6 weeks
   
       Use template if available: $AIWG_ROOT/templates/knowledge/knowledge-map-template.md
   
       Output: .aiwg/knowledge/knowledge-map-{domain}.md
       """
   )
   
   # Agent 2: Training Coordinator
   Task(
       subagent_type="training-coordinator",
       description="Create structured transfer plan",
       prompt="""
       Based on knowledge assessment, create transfer plan:
   
       Structure:
       1. Documentation Phase (Week 1)
          - Review existing docs
          - Identify and fill gaps
          - Create runbooks
   
       2. Shadowing Phase (Week 2-3)
          - 4-8 observation sessions
          - Knowledge holder leads, receiver observes
          - Q&A and note-taking
   
       3. Reverse Shadowing (Week 3-4)
          - 4-8 practice sessions
          - Receiver leads, holder observes
          - Feedback and correction
   
       4. Validation Phase (Week 4-5)
          - Practical scenarios
          - Independent operation test
          - Knowledge verification
   
       5. Handover Phase (Week 5-6)
          - Final checklist
          - Signoffs
          - Follow-up plan
   
       Adjust timeline based on:
       - Scope complexity
       - Availability constraints
       - {guidance if provided}
   
       Use template if available: $AIWG_ROOT/templates/knowledge/transfer-plan-template.md
   
       Output: .aiwg/knowledge/transfer-plan-{from}-to-{to}.md
       """
   )
   

3. Review and Confirm Scope:

   Task(
       subagent_type="project-manager",
       description="Review and validate transfer scope",
       prompt="""
       Read:
       - .aiwg/knowledge/knowledge-map-{domain}.md
       - .aiwg/knowledge/transfer-plan-{from}-to-{to}.md
   
       Validate:
       - Scope is realistic for timeline
       - Critical knowledge areas covered
       - Success criteria are measurable
       - Plan accounts for constraints
   
       Create gate decision:
       - GO: Proceed with transfer
       - ADJUST: Modify scope or timeline
       - ESCALATE: Needs management decision
   
       Output validation summary to transfer plan
       """
   )
   

Communicate Progress:

✓ Knowledge assessment complete
✓ Transfer scope defined: {X} knowledge areas, {Y} weeks estimated
✓ Transfer plan created: .aiwg/knowledge/transfer-plan-{from}-to-{to}.md

Step 2: Documentation Review and Knowledge Artifacts

Purpose: Compile and enhance documentation for knowledge transfer

Your Actions:

1. Inventory Existing Documentation:

   # Use Glob to find relevant docs
   Glob("**/*.md")
   Glob("**/*.txt")
   
   Filter for domain-relevant documentation
   Create inventory list
   

2. Launch Documentation Agents (parallel):

   # Agent 1: Documentation Archivist
   Task(
       subagent_type="documentation-archivist",
       description="Organize and review existing documentation",
       prompt="""
       Domain: {domain}
   
       Review existing documentation:
       1. Architecture documents
       2. Runbooks and procedures
       3. Configuration guides
       4. Troubleshooting guides
       5. Historical incident reports
   
       Assess each document:
       - Currency (up-to-date?)
       - Completeness (gaps?)
       - Clarity (understandable?)
       - Relevance (needed for transfer?)
   
       Create Documentation Inventory:
       - Core Docs (must review)
       - Reference Docs (good to know)
       - Archive Docs (historical context)
       - Missing Docs (gaps to fill)
   
       Organize in logical learning sequence
   
       Output: .aiwg/knowledge/docs/documentation-inventory.md
       """
   )
   
   # Agent 2: Subject Matter Expert (knowledge holder role)
   Task(
       subagent_type="subject-matter-expert",
       description="Identify and create missing documentation",
       prompt="""
       Acting as {from-member} (knowledge holder perspective)
   
       Based on documentation inventory, create missing critical docs:
   
       1. Runbooks for common operations:
          - Daily/weekly tasks
          - Deployment procedures
          - Rollback procedures
          - Monitoring and alerting
   
       2. Troubleshooting guides:
          - Common issues and solutions
          - Debugging techniques
          - Log analysis patterns
          - Performance tuning
   
       3. Architecture notes:
          - Design decisions and rationale
          - System boundaries and interfaces
          - Data flows and dependencies
          - Security considerations
   
       4. Tribal knowledge:
          - Undocumented gotchas
          - Historical context ("why it's this way")
          - Stakeholder relationships
          - Political/organizational context
   
       Focus on practical, hands-on knowledge needed for independent operation
   
       Output to: .aiwg/knowledge/docs/{category}/
       """
   )
   
   # Agent 3: Technical Writer
   Task(
       subagent_type="technical-writer",
       description="Enhance documentation clarity and completeness",
       prompt="""
       Review and enhance documentation for knowledge transfer:
   
       Improvements:
       1. Add missing context for newcomers
       2. Clarify technical jargon
       3. Add examples and scenarios
       4. Create quick reference guides
       5. Add diagrams where helpful
   
       Ensure documentation is:
       - Self-contained (minimal external references)
       - Progressive (basic → advanced)
       - Actionable (clear steps)
       - Verifiable (testable outcomes)
   
       Create consolidated reading list in order
   
       Output enhanced docs to: .aiwg/knowledge/docs/enhanced/
       """
   )
   

Communicate Progress:

⏳ Documentation review in progress...
  ✓ {X} existing documents inventoried
  ✓ {Y} documentation gaps identified
  ✓ {Z} new documents created
✓ Documentation package complete: .aiwg/knowledge/docs/

Step 3: Shadowing Phase (Receiver Observes)

Purpose: Knowledge receiver observes holder performing actual work

Your Actions:

1. Initialize Shadowing Sessions:

   # Create session structure
   mkdir -p .aiwg/knowledge/shadowing/sessions
   
   # Define 4-8 sessions based on knowledge areas
   For each critical knowledge area, allocate 1-2 sessions
   

2. Launch Shadowing Simulation (for each session):

   # For each shadowing session (4-8 total)
   Task(
       subagent_type="training-coordinator",
       description="Simulate shadowing session {N}",
       prompt="""
       Shadowing Session {N}
       Knowledge Area: {area from knowledge map}
       Duration: 1-2 hours (simulated)
   
       Simulate session where {from-member} demonstrates:
       1. Task execution (step-by-step)
       2. Decision points (what and why)
       3. Tool usage (specific commands/interfaces)
       4. Common issues (what to watch for)
       5. Best practices (efficiency tips)
   
       {to-member} perspective:
       - Observations noted
       - Questions asked
       - Concepts clarified
       - Confidence assessment (1-5)
   
       Create session log including:
       - Tasks demonstrated
       - Key decisions explained
       - Questions and answers
       - Key learnings captured
       - Follow-up items identified
       - Confidence rating
   
       Output: .aiwg/knowledge/shadowing/sessions/session-{N}-{area}.md
       """
   )
   

3. Synthesize Shadowing Learnings:

   Task(
       subagent_type="knowledge-manager",
       description="Synthesize shadowing phase learnings",
       prompt="""
       Read all shadowing session logs
   
       Create synthesis:
       1. Knowledge areas covered
       2. Key learnings consolidated
       3. Remaining questions
       4. Confidence progression (trend over sessions)
       5. Areas needing more practice
   
       Identify patterns:
       - Concepts requiring repetition
       - Complex areas needing breakdown
       - Tools requiring hands-on practice
   
       Recommend focus for reverse shadowing
   
       Output: .aiwg/knowledge/shadowing/shadowing-synthesis.md
       """
   )
   

Communicate Progress:

⏳ Shadowing phase in progress...
  ✓ Session 1: Database operations (confidence: 3/5)
  ✓ Session 2: Deployment procedures (confidence: 2/5)
  ✓ Session 3: Incident response (confidence: 4/5)
  ✓ Session 4: Performance tuning (confidence: 2/5)
✓ Shadowing complete: {X} sessions, average confidence: {Y}/5

Step 4: Reverse Shadowing Phase (Receiver Leads)

Purpose: Knowledge receiver performs tasks with holder observing

Your Actions:

1. Plan Reverse Shadowing Sessions:

   Based on shadowing synthesis, prioritize:
   - Low confidence areas (2/5 or below)
   - Critical operations
   - Complex procedures
   

2. Launch Reverse Shadowing (for each session):

   # For each reverse shadowing session (4-8 total)
   Task(
       subagent_type="learner",
       description="Simulate reverse shadowing session {N}",
       prompt="""
       Reverse Shadowing Session {N}
       Knowledge Area: {area}
       Receiver Leading: {to-member}
       Holder Observing: {from-member}
   
       Simulate {to-member} performing tasks:
       1. Task approach (how they tackle it)
       2. Decision making (choices and reasoning)
       3. Challenges faced (what's difficult)
       4. Holder interventions (when and why)
       5. Corrections made (learning moments)
   
       Holder feedback:
       - What went well
       - Areas for improvement
       - Specific corrections
       - Confidence assessment
   
       Success indicators:
       - Task completed correctly
       - Minimal interventions needed
       - Sound reasoning demonstrated
   
       Create session log:
       - Tasks performed
       - Interventions required
       - Feedback provided
       - Outcome (SUCCESS, PARTIAL, NEEDS_PRACTICE)
       - Confidence growth
   
       Output: .aiwg/knowledge/shadowing/reverse/session-{N}-{area}.md
       """
   )
   

3. Assess Progress and Readiness:

   Task(
       subagent_type="training-coordinator",
       description="Assess reverse shadowing progress",
       prompt="""
       Read all reverse shadowing sessions
   
       Assess readiness:
       1. Tasks completed successfully (%)
       2. Intervention frequency (trending down?)
       3. Confidence ratings (trending up?)
       4. Decision quality (sound reasoning?)
   
       For each knowledge area:
       - Status: READY | NEEDS_PRACTICE | NOT_READY
       - Remaining gaps
       - Recommended actions
   
       Overall assessment:
       - Ready for validation: YES/NO
       - Areas needing more practice
       - Estimated additional time needed
   
       Output: .aiwg/knowledge/shadowing/reverse/readiness-assessment.md
       """
   )
   

Communicate Progress:

⏳ Reverse shadowing in progress...
  ✓ Session 1: Database operations (SUCCESS, minimal intervention)
  ✓ Session 2: Deployment procedures (PARTIAL, 2 interventions)
  ✓ Session 3: Incident response (SUCCESS, no intervention)
  ⚠️ Session 4: Performance tuning (NEEDS_PRACTICE, multiple interventions)
✓ Reverse shadowing complete: 75% success rate

Step 5: Knowledge Validation and Practical Testing

Purpose: Validate knowledge acquisition through realistic scenarios

Your Actions:

1. Create Validation Scenarios:

   Task(
       subagent_type="test-architect",
       description="Design validation scenarios",
       prompt="""
       Based on knowledge domain {domain}, create 4 validation scenarios:
   
       Scenario 1: Routine Operation
       - Common daily/weekly task
       - Expected to complete independently
       - Time limit: reasonable for task
   
       Scenario 2: Troubleshooting
       - Realistic problem to diagnose and fix
       - Tests analytical skills
       - Multiple solution paths acceptable
   
       Scenario 3: Teach-Back
       - Explain concept to simulated junior member
       - Tests depth of understanding
       - Must be accurate and clear
   
       Scenario 4: Novel Situation
       - New problem not explicitly covered
       - Tests knowledge application
       - Reasonable extrapolation expected
   
       Each scenario includes:
       - Context and setup
       - Success criteria
       - Evaluation rubric
       - Time expectations
   
       Output: .aiwg/knowledge/validation/validation-scenarios.md
       """
   )
   

2. Execute Validation Tests (parallel where possible):

   # For each validation scenario
   Task(
       subagent_type="learner",
       description="Execute validation scenario {N}",
       prompt="""
       As {to-member}, complete validation scenario {N}
   
       Demonstrate:
       1. Understanding of the problem
       2. Systematic approach
       3. Correct solution or diagnosis
       4. Appropriate tool usage
       5. Documentation of actions
   
       For teach-back scenario:
       - Explain clearly
       - Use examples
       - Check understanding
   
       For novel situation:
       - Show problem-solving process
       - Use available resources
       - Apply learned principles
   
       Document:
       - Approach taken
       - Solution provided
       - Time taken
       - Confidence level
       - Resources consulted
   
       Output: .aiwg/knowledge/validation/scenario-{N}-results.md
       """
   )
   
   # Parallel evaluation by holder
   Task(
       subagent_type="subject-matter-expert",
       description="Evaluate validation scenarios",
       prompt="""
       As {from-member}, evaluate {to-member}'s performance
   
       For each scenario:
       - Accuracy (correct solution?)
       - Approach (systematic and logical?)
       - Efficiency (reasonable time?)
       - Independence (minimal help needed?)
       - Documentation (clear and complete?)
   
       Rating scale:
       - EXCELLENT: Exceeds expectations
       - PASS: Meets requirements
       - CONDITIONAL: Mostly correct, minor gaps
       - FAIL: Significant gaps, more practice needed
   
       Provide specific feedback:
       - What was done well
       - Areas for improvement
       - Recommendations
   
       Overall readiness assessment:
       - READY for independent operation
       - READY with support period
       - NOT READY, need more practice
   
       Output: .aiwg/knowledge/validation/evaluation-results.md
       """
   )
   

Communicate Progress:

⏳ Validation testing in progress...
  ✓ Scenario 1 (Routine): PASS
  ✓ Scenario 2 (Troubleshooting): PASS
  ✓ Scenario 3 (Teach-Back): EXCELLENT
  ⚠️ Scenario 4 (Novel): CONDITIONAL (minor gaps noted)
✓ Validation complete: 3/4 PASS or better

Step 6: Handover Checklist and Signoff

Purpose: Complete formal handover with all parties signing off

Your Actions:

1. Generate Handover Checklist:

   Task(
       subagent_type="project-manager",
       description="Create comprehensive handover checklist",
       prompt="""
       Create handover checklist for:
       - Domain: {domain}
       - From: {from-member}
       - To: {to-member}
       - Duration: {weeks from start to now}
   
       Checklist sections:
   
       1. Documentation
          - All docs reviewed: YES/NO
          - Gaps addressed: YES/NO
          - Bookmarks/access: YES/NO
   
       2. Practical Skills
          - Routine tasks: {validation results}
          - Troubleshooting: {validation results}
          - Emergency procedures: UNDERSTOOD/PRACTICED
   
       3. Knowledge Validation
          - Scenarios passed: {X}/4
          - Teach-back successful: YES/NO
          - Holder confidence: {rating}
   
       4. Access and Permissions
          - System access: GRANTED/PENDING
          - Tool access: GRANTED/PENDING
          - Communication channels: ADDED/PENDING
   
       5. Operational Handoff
          - On-call rotation: UPDATED/PENDING
          - Responsibility matrix: UPDATED/PENDING
          - Stakeholder notification: SENT/PENDING
   
       6. Follow-Up Plan
          - 1-week check-in: {date}
          - 1-month check-in: {date}
          - Support period: {duration}
   
       7. Residual Gaps (if any)
          - List with severity and remediation plan
   
       Use template if available: $AIWG_ROOT/templates/knowledge/handover-checklist-template.md
   
       Output: .aiwg/knowledge/handover-checklist-{domain}.md
       """
   )
   

2. Collect Signoffs:

   Task(
       subagent_type="project-manager",
       description="Collect handover signoffs",
       prompt="""
       Document signoffs for handover:
   
       Required signatures:
       1. Knowledge Receiver ({to-member}):
          "I am confident in my ability to perform {domain} responsibilities independently"
          Confidence level: {1-5}
          Concerns (if any): {list}
   
       2. Knowledge Holder ({from-member}):
          "I am confident the receiver has the knowledge to succeed independently"
          Confidence level: {1-5}
          Recommendations: {list}
   
       3. Project Manager:
          "Knowledge transfer is complete and receiver is ready for independent operation"
          Decision: APPROVED / CONDITIONAL / NOT_APPROVED
   
       Conditional requirements (if CONDITIONAL):
       - What must be completed
       - Timeline for completion
       - Re-validation plan
   
       Add signatures to handover checklist
       """
   )
   

3. Generate Final Report:

   Task(
       subagent_type="knowledge-manager",
       description="Generate knowledge transfer completion report",
       prompt="""
       Create comprehensive transfer report including:
   
       1. Executive Summary
          - Transfer status: COMPLETE/PARTIAL/INCOMPLETE
          - Readiness: READY/CONDITIONAL/NOT_READY
          - Key outcomes
   
       2. Transfer Summary
          - Scope (knowledge areas covered)
          - Timeline (planned vs actual)
          - Methods (shadowing, documentation, validation)
   
       3. Knowledge Acquisition Metrics
          - Shadowing sessions: {count}
          - Reverse shadowing: {count}
          - Validation scenarios: {passed}/{total}
          - Confidence progression: {start} → {end}
   
       4. Documentation Improvements
          - Docs created: {count}
          - Docs enhanced: {count}
          - Remaining gaps: {list}
   
       5. Validation Results
          - Detailed scenario outcomes
          - Evaluator feedback
          - Areas of strength
          - Areas for improvement
   
       6. Lessons Learned
          - What worked well
          - What could improve
          - Recommendations for future transfers
   
       7. Follow-Up Plan
          - Check-in schedule
          - Support arrangements
          - Escalation path
   
       8. Risk Assessment
          - Operational risks
          - Mitigation strategies
          - Contingency plans
   
       Output: .aiwg/reports/knowledge-transfer-report-{domain}.md
       """
   )
   

Communicate Progress:

✓ Handover checklist complete: .aiwg/knowledge/handover-checklist-{domain}.md
✓ All parties signed off
✓ Transfer report generated: .aiwg/reports/knowledge-transfer-report-{domain}.md

Quality Gates

Before marking workflow complete, verify:

• Knowledge assessment documented
• Transfer plan created and followed
• Documentation gaps addressed
• Shadowing sessions completed (minimum 4)
• Reverse shadowing completed (minimum 4)
• Validation scenarios passed (≥75%)
• Handover checklist complete
• All required signoffs obtained
• Follow-up plan established

User Communication

At start: Confirm understanding and outline process

Understood. I'll orchestrate the knowledge transfer from {from-member} to {to-member} for {domain}.

This will include:
- Knowledge assessment and gap analysis
- Documentation review and enhancement
- Shadowing sessions (observation)
- Reverse shadowing (practice)
- Validation testing
- Formal handover and signoff

Expected duration: 30-45 minutes orchestration.
Real-world timeline: 2-6 weeks for actual transfer.

Starting orchestration...

During: Update progress with clear indicators

✓ = Complete
⏳ = In progress
⚠️ = Attention needed
❌ = Failed/blocked

At end: Summary report with status and next steps

─────────────────────────────────────────────
Knowledge Transfer Complete
─────────────────────────────────────────────

**Transfer**: {from-member} → {to-member}
**Domain**: {domain}
**Status**: COMPLETE
**Readiness**: READY FOR INDEPENDENT OPERATION

**Summary**:
✓ Knowledge gaps identified and addressed
✓ Documentation: {X} docs created/updated
✓ Shadowing: {Y} sessions completed
✓ Validation: {Z}/4 scenarios passed
✓ Handover: All parties signed off

**Confidence Assessment**:
- Receiver confidence: 4/5
- Holder confidence: 4/5
- Manager approval: APPROVED

**Follow-Up Plan**:
- 1-week check-in: {date}
- 1-month review: {date}
- Support period: {from-member} available for {duration}

**Artifacts Generated**:
- Knowledge Map: .aiwg/knowledge/knowledge-map-{domain}.md
- Transfer Plan: .aiwg/knowledge/transfer-plan-{from}-to-{to}.md
- Documentation: .aiwg/knowledge/docs/
- Validation Results: .aiwg/knowledge/validation/
- Handover Checklist: .aiwg/knowledge/handover-checklist-{domain}.md
- Final Report: .aiwg/reports/knowledge-transfer-report-{domain}.md

**Next Steps**:
- Update team roster and responsibilities
- Schedule follow-up check-ins
- Monitor initial independent operation
- Address any residual gaps per remediation plan

─────────────────────────────────────────────

Error Handling

Team Member Not Found:

⚠️ Team member not found in roster
Proceeding with provided names: {from-member} → {to-member}

Note: Consider updating .aiwg/team/team-profile.yaml

Knowledge Domain Unclear:

⚠️ Knowledge domain not specified

Defaulting to: "all responsibilities"
This may extend timeline and scope.

Recommendation: Specify domain for focused transfer
Example: "backend-api", "deployment", "security"

Validation Failure:

❌ Validation scenario failed: {scenario}

Result: {failure-reason}
Impact: Receiver not ready for independent operation

Recommendations:
1. Additional practice in {area}
2. Review relevant documentation
3. Schedule extra reverse shadowing session
4. Re-attempt validation after practice

Insufficient Confidence:

⚠️ Low confidence detected

Receiver confidence: {X}/5 (target: ≥3)
Holder confidence: {Y}/5 (target: ≥3)

Actions:
1. Identify specific concern areas
2. Provide additional shadowing/practice
3. Consider extended support period
4. Document contingency plans

Timeline Overrun:

⚠️ Transfer taking longer than planned

Original estimate: {X} weeks
Current duration: {Y} weeks

Factors:
- Complexity underestimated
- Availability constraints
- Additional gaps discovered

Recommendation: Adjust timeline and expectations

Success Criteria

This orchestration succeeds when:

• Knowledge gaps identified and documented
• Transfer scope agreed by all parties
• Documentation complete and accessible
• Minimum 4 shadowing sessions completed
• Minimum 4 reverse shadowing sessions completed
• ≥75% validation scenarios passed
• Receiver confidence ≥3/5
• Holder confidence ≥3/5
• Handover checklist signed off
• Follow-up plan established

Metrics to Track

During orchestration, track:

• Documentation coverage: % of knowledge areas documented
• Shadowing completion: # sessions completed vs planned
• Confidence progression: Rating trend over time
• Validation pass rate: % scenarios passed first attempt
• Time to competency: Weeks from start to signoff

References

Templates (via $AIWG_ROOT):

• Knowledge Map: templates/knowledge/knowledge-map-template.md
• Transfer Plan: templates/knowledge/transfer-plan-template.md
• Shadowing Log: templates/knowledge/shadowing-log-template.md
• Validation Checklist: templates/knowledge/knowledge-validation-checklist.md
• Handover Checklist: templates/knowledge/handover-checklist-template.md

Related Commands:

• team-roster - Update team responsibilities
• update-oncall - Modify on-call schedules
• flow-onboarding - Full team member onboarding

Best Practices:

• docs/knowledge-transfer-best-practices.md
• docs/shadowing-techniques.md
• docs/validation-scenario-design.md