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Agent Skill · 研究检索

agent-knowledge-transfer(Agent 知识转移)

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。

agent-knowledge-transfer 是研究检索类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为执行命令;许可证为 MIT-0,第三方扫描有提醒项,按安装量在研究检索类的 73,675 个 Skill 里排第 32,689。

总安装 2,472周安装 101GitHub Stars 公开资料未说明下载 792核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT-0
版本
1.0.0

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

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

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。

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 OpenClaw;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 openclaw skills install agent-knowledge-transfer;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要执行命令,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

agent-knowledge-transfer 怎么安装?

在终端执行 openclaw skills install agent-knowledge-transfer。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

agent-knowledge-transfer 支持哪些 AI 工具?

公开资料标注支持 OpenClaw。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

agent-knowledge-transfer 需要什么权限?

权限级别是执行命令。安装流程涉及命令执行,可能通过 openclaw skills install agent-knowledge-transfer 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

agent-knowledge-transfer 是免费的吗?

来源标注的许可证是 MIT-0。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

agent-knowledge-transfer 用的人多吗?

公开数据是累计安装 2,472 次,近一周安装 101 次,下载 792 次。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

agent-knowledge-transfer 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

值得选的地方和要先想清楚的地方

值得选的地方

  • 专注 OpenClaw 一种宿主,触发方式和使用习惯不用来回切换。
  • 许可证明确为 MIT-0,商用和分发边界好判断。

先想清楚的地方

  • 需要执行命令,装到常用环境前要先评估影响面。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 OpenClaw,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 不能接受 Skill 在你机器上执行命令的人。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
agent-knowledge-transfer

Agent 知识转移 · 本页

2,472—执行命令MIT-0有提醒

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

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

平台分布

OpenClaw

88.21%
按下载量换算699

安全审计

VirusTotal

可疑

ClawScan

可疑

Static analysis

通过

权限和风险

执行命令

安装流程涉及命令执行,可能通过 openclaw skills install agent-knowledge-transfer 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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