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agent-knowledge-transferAgent 知识转移

Agent Skill

agent-knowledge-transfer 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

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安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:agent-knowledge-transfer(Agent 知识转移)
来源仓库:https://github.com/stefanferreira/agent-knowledge-transfer
安装命令:
openclaw skills install agent-knowledge-transfer
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install agent-knowledge-transfer

简介

用于将代理转化为具有完整身份、技能和上下文的智能体。

  • 适合需要构建长期记忆与人格特征的复杂代理场景。
  • 通过结构化协议实现知识迁移,支持身份与技能封装。
  • 安装前需确认权限范围及是否涉及文件读写或网络访问。
  • 建议结合原始文档核验具体配置与使用方式。agent-knowledge-transfer 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

name
agent-knowledge-transfer
description
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

# 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

# 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

# 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

# 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

# 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

# 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

# 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

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

Automation Script

Use the automated knowledge transfer script:

# 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"

  1. "What have you learned?"

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

  1. "What is your role?"

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

  1. "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:

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

2. Required Tool Permissions:

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

3. Complete File Set:

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

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

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