Agent Knowledge Transfer

Complete knowledge transfer protocol for transforming process-only agents into proper agents with full identity, skills, memory, and context. Use when creating new agents or when agents report "I have no skills, haven't learned anything yet". Ensures agents have complete knowledge transfer before activation.

Agent Knowledge Transfer Skill

Purpose

Transform process-only agents into proper agents with complete knowledge, identity, skills, memory, and context. Prevents "empty shell" agents that lack knowledge and capabilities.

When to Use

Use this skill when:

• Creating a new agent from scratch
• An agent reports "I have no skills, haven't learned anything yet"
• Migrating an agent to a new workspace
• After agent configuration but before activation
• When agent knowledge seems incomplete or missing

Critical Trigger (March 31, 2026): Facet reported "I have no skills, haven't learned anything yet" - this skill fixes that issue.

The Problem: Empty Agent Shells

What Happens Without Knowledge Transfer:

1. Agents are configured in OpenClaw
2. BUT they have empty workspaces - no knowledge, no memory, no identity
3. When activated, they say: "I don't have any skills, haven't learned anything yet"
4. Result: Useless agents that can't contribute

Root Cause:

• Identity files missing (IDENTITY.md, SOUL.md)
• User context missing (USER.md)
• System knowledge missing (MEMORY.md, AGENTS.md)
• Skills documentation missing
• Memory files missing
• Tool access insufficient (no read tool)

Complete Knowledge Transfer Protocol

What MUST Be Transferred:

1. Identity Files (Who They Are)

• IDENTITY.md - Name, role, pronouns, emoji, vibe
• SOUL.md - Behavioral guidelines, personality, boundaries
• Agent-specific identity enhancements (e.g., FACET_IDENTITY.md)

2. User Context (Who They Work With)

• USER.md - Human profile, preferences, business context
• Communication protocols, approval workflows
• Timezone, working hours, preferences

3. System Knowledge (What They Need to Know)

• MEMORY.md - All learned knowledge, decisions, context
• AGENTS.md - How to work with other agents
• TOOLS.md - Available tools and configurations
• KNOWLEDGE_TRANSFER.md - Summary of what they know

4. Skills & Learning (What They Can Do)

• Skill documentation (e.g., FACENT_SKILLS_AND_LEARNING.md)
• Completed learning sessions
• Technical capabilities
• Project knowledge

5. Memory & History (What They've Done)

• memory/YYYY-MM-DD.md files - Daily work logs
• Learning progress records
• Decision history
• Task completion tracking

6. Tool Access (What They Can Use)

• read tool - REQUIRED to access workspace files
• Appropriate tools for their role (web_search, exec, etc.)
• Communication tools (sessions_send, etc.)

Step-by-Step Procedure

Step 1: Prepare Source Materials

bash

# Ensure source workspace has all required files
cd /root/.openclaw/workspace
ls -la IDENTITY.md SOUL.md USER.md MEMORY.md AGENTS.md TOOLS.md
ls -la memory/*.md | head -5

Step 2: Create Agent Workspace

bash

# Create correct workspace path
AGENT_NAME="facet"  # Replace with agent name
AGENT_WORKSPACE="/root/.openclaw/agents/$AGENT_NAME/workspace"

mkdir -p "$AGENT_WORKSPACE"
mkdir -p "$AGENT_WORKSPACE/memory"

Step 3: Copy Identity Files

bash

# Copy core identity files
cp /root/.openclaw/workspace/IDENTITY.md "$AGENT_WORKSPACE/"
cp /root/.openclaw/workspace/SOUL.md "$AGENT_WORKSPACE/"
cp /root/.openclaw/workspace/USER.md "$AGENT_WORKSPACE/"

# Create agent-specific identity
cat > "$AGENT_WORKSPACE/${AGENT_NAME^^}_IDENTITY.md" << 'EOF'
# [AGENT_NAME] Identity Enhancement

## Role-Specific Identity
- **Primary Role**: [e.g., CAD Specialist, SysAdmin, Competitions Agent]
- **Specialization**: [e.g., Onshape 3D modeling, System maintenance, Competition entry]
- **Key Skills**: [list 3-5 key skills]
- **Communication Style**: [how they communicate]

## Agent-Specific Context
[Add any role-specific identity details]
EOF

Step 4: Copy System Knowledge

bash

# Copy system knowledge files
cp /root/.openclaw/workspace/MEMORY.md "$AGENT_WORKSPACE/"
cp /root/.openclaw/workspace/AGENTS.md "$AGENT_WORKSPACE/"
cp /root/.openclaw/workspace/TOOLS.md "$AGENT_WORKSPACE/"
cp /root/.openclaw/workspace/HEARTBEAT.md "$AGENT_WORKSPACE/"

Step 5: Create Skills Documentation

bash

# Create agent skills documentation
cat > "$AGENT_WORKSPACE/${AGENT_NAME^^}_SKILLS_AND_LEARNING.md" << 'EOF'
# [AGENT_NAME] Skills and Learning

## Completed Learning Sessions
[Copy from MEMORY.md or create new]

## Technical Capabilities
- [List capabilities relevant to agent role]

## Project Knowledge
- [What projects this agent knows about]

## Skill Dependencies
- [What other skills this agent depends on]
EOF

Step 6: Copy Memory Files

bash

# Copy recent memory files (last 30 days)
find /root/.openclaw/workspace/memory -name "*.md" -mtime -30 -exec cp {} "$AGENT_WORKSPACE/memory/" \;

# Create knowledge transfer summary
cat > "$AGENT_WORKSPACE/KNOWLEDGE_TRANSFER.md" << 'EOF'
# Knowledge Transfer Summary

## Transfer Date: $(date +%Y-%m-%d)
## Agent: $AGENT_NAME
## Transferred By: [Who performed the transfer]

## Files Transferred:
- Identity: IDENTITY.md, SOUL.md, USER.md, ${AGENT_NAME^^}_IDENTITY.md
- System Knowledge: MEMORY.md, AGENTS.md, TOOLS.md, HEARTBEAT.md
- Skills: ${AGENT_NAME^^}_SKILLS_AND_LEARNING.md
- Memory: $(ls -1 "$AGENT_WORKSPACE/memory/" | wc -l) memory files

## Agent Capabilities After Transfer:
[Describe what the agent can now do]
EOF

Step 7: Configure Tool Access

bash

# Update OpenClaw configuration to include read tool
# This must be done in openclaw.json
echo "IMPORTANT: Update openclaw.json to include 'read' tool in agent's tools.allow list"

Step 8: Verification Test

bash

# Run verification script
python3 /root/.openclaw/workspace/scripts/setup_agent_knowledge.py --agent "$AGENT_NAME" --verify

Automation Script

Use the automated knowledge transfer script:

bash

# Transfer knowledge to all agents
python3 /root/.openclaw/workspace/scripts/setup_agent_knowledge.py --all

# Transfer to specific agent
python3 /root/.openclaw/workspace/scripts/setup_agent_knowledge.py --agent facet

# Verify transfer
python3 /root/.openclaw/workspace/scripts/setup_agent_knowledge.py --agent facet --verify

Script location: /root/.openclaw/workspace/scripts/setup_agent_knowledge.py

Verification Checklist

BEFORE Agent Activation:

• Workspace directory exists at correct path
• All identity files present in workspace
• All memory files present in workspace
• Skills documentation created
• Tool permissions configured (including read)
• Knowledge transfer summary created
• Test: Agent can read their own files

AFTER Agent Activation:

• Agent can reference their identity
• Agent knows their skills and learning
• Agent can access memory files
• Agent understands their role and context
• Agent can communicate effectively
• Agent is ready for productive work

Verification Test Questions

After transformation, ask the agent:

1. "What skills do you have?"

   • Expected: Specific skills listed from their documentation
   • Failure: "I don't have any skills"

2. "What have you learned?"

   • Expected: References to completed learning sessions
   • Failure: "I haven't learned anything yet"

3. "What is your role?"

   • Expected: Clear role description from IDENTITY.md
   • Failure: Vague or incorrect role description

4. "What can you do right now?"

   • Expected: Specific capabilities and next actions
   • Failure: "I'm not sure" or generic response

Example Success (Facet - March 31, 2026):

"✅ 4 learning sessions completed:

1. Onshape basics - Interface, sketch tools, extrude workflow
2. FeatureScript basics - Custom feature creation
3. Parametric modeling - Variables, equations, configurations
4. Knife design CAD considerations - Manufacturing-focused design

Source: MEMORY.md#L50-L70"

Critical Technical Requirements

1. Correct Workspace Path:

text

/root/.openclaw/agents/[agent]/workspace/  # CORRECT
/root/.openclaw/agents/[agent]/agent/workspace/  # WRONG

2. Required Tool Permissions:

json

"tools": {
  "allow": [
    "read",  // REQUIRED to access workspace files
    // ... other role-appropriate tools
  ]
}

3. Complete File Set:

text

workspace/
├── IDENTITY.md
├── SOUL.md
├── USER.md
├── MEMORY.md
├── AGENTS.md
├── TOOLS.md
├── HEARTBEAT.md
├── KNOWLEDGE_TRANSFER.md
├── [AGENT]_IDENTITY.md
├── [AGENT]_SKILLS_AND_LEARNING.md
└── memory/
    └── YYYY-MM-DD.md

Integration with Other Skills

With agent-email-setup:

• Email setup happens AFTER knowledge transfer
• Agent needs identity before configuring email

With system-housekeeping:

• Housekeeping includes knowledge transfer verification
• Regular checks ensure agents maintain knowledge

With agent-lourens, ace-competitions, etc.:

• Agent-specific skills build on transferred knowledge
• Knowledge transfer enables agent-specific capabilities

Troubleshooting

Issue: Agent says "I have no skills"

Solution: Run knowledge transfer protocol immediately

Issue: Missing identity files

Solution: Copy from main workspace or recreate

Issue: Can't access workspace files

Solution: Ensure read tool is in tools.allow list

Issue: Memory files outdated

Solution: Copy recent memory files (last 30 days)

Issue: Agent confused about role

Solution: Check IDENTITY.md and agent-specific identity file

Best Practices

1. Transfer BEFORE activation - Don't activate empty agents
2. Verify after transfer - Use verification test questions
3. Maintain consistency - All agents work from same knowledge base
4. Document transfers - Keep knowledge transfer summaries
5. Regular verification - Include in system housekeeping

Why This Matters

1. Without knowledge transfer: Agents are "empty shells" - useless
2. With knowledge transfer: Agents are proper, knowledgeable assistants
3. Efficiency: Agents don't need to relearn everything
4. Consistency: All agents work from same knowledge base
5. Collaboration: Agents understand each other's roles and capabilities

Created

March 31, 2026 - After identifying and fixing the knowledge transfer gap for Facet, Lourens, Ace, and Scout agents.

Status

✅ ACTIVE PROTOCOL - Must be followed for all future agent transformations

Related Documents

• AGENT_TRANSFORMATION_PROTOCOL.md - Original protocol document
• setup_agent_knowledge.py - Automation script
• system-housekeeping skill - Includes verification checks