Free SKILL.md scraped from GitHub. Clone the repo or copy the file directly into your Claude Code skills directory.
npx versuz@latest install jmagly-aiwg-plugins-sdlc-skills-flow-knowledge-transfergit clone https://github.com/jmagly/aiwg.gitcp aiwg/SKILL.MD ~/.claude/skills/jmagly-aiwg-plugins-sdlc-skills-flow-knowledge-transfer/SKILL.md---
namespace: aiwg
name: flow-knowledge-transfer
platforms: [all]
description: Orchestrate Knowledge Transfer flow with assessment, documentation, shadowing, validation, and handover
commandHint:
argumentHint: <from-member> <to-member> [domain] [--guidance "text"] [--interactive]
allowedTools: Task, Read, Write, Glob, TodoWrite
model: opus
category: sdlc-orchestration
orchestration: true
---
# 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`