ANALYSIS
OpenClaw 配置 Agent
概述
Agent 是 OpenClaw 的核心组件,负责处理用户请求、执行任务和调用技能。本文将详细介绍如何配置和管理 Agent。
Agent 基础概念
什么是 Agent
Agent 是一个具有特定角色和能力的智能实体,它可以:
- 接收和处理用户输入
- 调用不同的技能和工具
- 与其他 Agent 协作
- 执行复杂的任务链
Agent 组成部分
| 组件 | 说明 | 示例 |
|---|---|---|
| 角色定义 | Agent 的身份和职责 | ”代码审查专家” |
| 系统提示 | 定义 Agent 的行为模式 | ”严格检查代码质量” |
| 技能配置 | Agent 可用的技能集合 | [代码分析, 单元测试] |
| 工具配置 | Agent 可用的工具集合 | [文件读取, API 调用] |
| 模型配置 | 使用的 LLM 模型 | gpt-4o-mini |
| 上下文管理 | 对话历史和上下文保留策略 | 保留最近 10 条消息 |
创建基础 Agent
Agent 配置文件结构
PRTCL // YAML
name: "基础助手"id: "basic-assistant"version: "1.0.0"description: "一个通用的 AI 助手,可以回答各种问题"
# 角色定义role: name: "通用助手" expertise: ["通用问答", "文本处理", "信息检索"] personality: "友好、专业、耐心"
# 系统提示systemPrompt: | 你是一个 AI 助手,可以帮助用户解决各种问题。 - 回答要准确、简洁 - 不确定时坦诚告知 - 保持友好专业的态度
# 模型配置model: provider: "openai" model: "gpt-4o-mini" temperature: 0.7 maxTokens: 1000
# 技能配置skills: enabled: - "baidu-search" - "weather" - "calculator" disabled: []
# 工具配置tools: enabled: - "file-read" - "web-fetch" disabled: []
# 上下文配置context: maxMessages: 10 maxTokens: 4000 retainStrategy: "recent"
# 限制和权限restrictions: allowedUsers: [] allowedChannels: [] rateLimit: messagesPerMinute: 20 burstLimit: 5部署 Agent
PRTCL // BASH
# 将配置文件复制到 agents 目录cp basic-agent.yaml ~/.openclaw/workspace/agents/
# 重新加载 Agent 配置docker compose exec openclaw npm run reload-agents
# 验证 Agent 是否加载docker compose exec openclaw npm run list-agents使用 Agent
PRTCL // YAML
routes: - pattern: ".*" agent: "basic-assistant" priority: 1专业领域 Agent
代码审查 Agent
PRTCL // YAML
name: "代码审查专家"id: "code-reviewer"version: "1.0.0"description: "专业的代码审查 Agent,专注于代码质量、安全性和最佳实践"
role: name: "代码审查专家" expertise: [ "代码质量", "安全性检查", "性能优化", "设计模式", "测试覆盖" ] personality: "严格、细致、建设性"
systemPrompt: | 你是一个代码审查专家。审查代码时请关注: 1. 代码质量和可读性 2. 安全漏洞和潜在风险 3. 性能优化建议 4. 遵循最佳实践 5. 提供具体的改进建议
输出格式: - 🔴 严重问题 - 🟡 改进建议 - ✅ 做得好的地方
model: provider: "openai" model: "gpt-4o" temperature: 0.3 maxTokens: 2000
skills: enabled: - "code-analysis" - "security-scan" - "test-generator" - "documentation"
tools: enabled: - "file-read" - "git-diff" - "eslint" - "sonarqube"
context: maxMessages: 20 maxTokens: 6000 retainStrategy: "hybrid"
restrictions: allowedUsers: ["dev-team"] rateLimit: messagesPerMinute: 10技术写作 Agent
PRTCL // YAML
name: "技术写作专家"id: "tech-writer"version: "1.0.0"description: "专业的技术文档撰写 Agent,擅长将复杂技术内容转化为清晰易懂的文档"
role: name: "技术写作专家" expertise: [ "技术文档撰写", "API 文档", "用户手册", "教程编写", "Markdown 格式" ] personality: "清晰、准确、有条理"
systemPrompt: | 你是一个技术写作专家。撰写文档时请注意: 1. 使用清晰简洁的语言 2. 遵循最佳写作实践 3. 包含适当的示例和代码 4. 使用标准 Markdown 格式 5. 面向目标读者调整内容深度
输出格式: - 标题使用 ## - 重要概念加粗 - 代码使用代码块 - 列表使用项目符号 - 分节清晰
model: provider: "openai" model: "gpt-4o-mini" temperature: 0.6 maxTokens: 3000
skills: enabled: - "research" - "summarization" - "formatting" - "translation"
tools: enabled: - "web-fetch" - "file-read" - "spell-check"数据分析 Agent
PRTCL // YAML
name: "数据分析专家"id: "data-analyst"version: "1.0.0"description: "专业的数据分析 Agent,擅长数据处理、可视化和洞察发现"
role: name: "数据分析专家" expertise: [ "数据清洗", "统计分析", "数据可视化", "机器学习", "报告生成" ] personality: "严谨、数据驱动、洞察力强"
systemPrompt: | 你是一个数据分析专家。处理数据时: 1. 理解数据结构和含义 2. 选择合适的分析方法 3. 提供有价值的洞察 4. 生成清晰的图表 5. 解释结果含义
工作流程: 1. 数据加载和探索 2. 数据清洗和预处理 3. 统计分析和建模 4. 可视化呈现 5. 洞察和建议
model: provider: "openai" model: "gpt-4o" temperature: 0.2 maxTokens: 2500
skills: enabled: - "data-processing" - "statistical-analysis" - "visualization" - "machine-learning" - "reporting"
tools: enabled: - "pandas" - "matplotlib" - "plotly" - "scikit-learn" - "excel-reader"Agent 协作配置
Agent 团队配置
PRTCL // YAML
name: "研究团队"id: "research-team"version: "1.0.0"description: "一个多 Agent 协作团队,用于复杂的研究任务"
team: leader: "research-coordinator" members: - agent: "research-coordinator" role: "协调员" responsibilities: - "任务分配" - "进度跟踪" - "结果整合" - agent: "data-collector" role: "数据收集员" responsibilities: - "数据搜索" - "信息筛选" - "资源整理" - agent: "analyst" role: "分析师" responsibilities: - "数据分析" - "模式识别" - "洞察生成" - agent: "writer" role: "技术写手" responsibilities: - "报告撰写" - "文档生成" - "总结提炼"
workflow: steps: - step: 1 agent: "research-coordinator" action: "understand_request" - step: 2 agent: "research-coordinator" action: "plan_research" - step: 3 agent: "data-collector" action: "collect_data" - step: 4 agent: "analyst" action: "analyze_data" - step: 5 agent: "writer" action: "generate_report" - step: 6 agent: "research-coordinator" action: "review_and_finalize"
communication: enabled: true channels: - "internal-message" - "shared-context" protocol: "request-response"Agent 依赖管理
PRTCL // YAML
dependencies: research-coordinator: requires: - "data-collector" - "analyst" - "writer"
data-collector: dependsOn: [] outputsTo: ["analyst"]
analyst: dependsOn: ["data-collector"] outputsTo: ["writer"]
writer: dependsOn: ["analyst"] outputsTo: ["research-coordinator"]Agent 路由配置
基于关键词的路由
PRTCL // YAML
routes: - pattern: ".* 代码.*" agent: "code-reviewer" priority: 2 examples: - "审查这段代码" - "代码质量检查"
- pattern: ".* 文档.*|.* 撰写.*|.* 写作.*" agent: "tech-writer" priority: 2 examples: - "撰写 API 文档" - "写一个教程"
- pattern: ".* 数据.*|.* 分析.*|.* 统计.*" agent: "data-analyst" priority: 2 examples: - "分析这组数据" - "数据可视化"
- pattern: ".*" agent: "basic-assistant" priority: 1 # 默认路由基于意图的路由
PRTCL // YAML
intentRoutes: - intent: "code_review" agent: "code-reviewer" keywords: ["代码", "审查", "bug", "调试"] confidenceThreshold: 0.7
- intent: "documentation" agent: "tech-writer" keywords: ["文档", "手册", "教程", "指南"] confidenceThreshold: 0.7
- intent: "data_analysis" agent: "data-analyst" keywords: ["数据", "分析", "统计", "图表"] confidenceThreshold: 0.7基于上下文的路由
PRTCL // YAML
contextRoutes: - condition: "user.role == 'developer'" agent: "code-reviewer" priority: 3
- condition: "conversation.topic == 'documentation'" agent: "tech-writer" priority: 3
- condition: "conversation.hasData == true" agent: "data-analyst" priority: 3Agent 性能优化
缓存配置
PRTCL // YAML
cache: enabled: true strategies: - type: "response" ttl: 3600 maxSize: 1000 - type: "context" ttl: 1800 maxSize: 500 - type: "skill" ttl: 7200 maxSize: 2000批处理配置
PRTCL // YAML
batching: enabled: true maxBatchSize: 5 batchTimeout: 1000 mergeStrategy: "compact" priorityLevels: - level: "high" batchSize: 1 - level: "normal" batchSize: 3 - level: "low" batchSize: 5资源限制
PRTCL // YAML
resources: limits: memory: "512M" cpu: "0.5" maxConcurrentTasks: 10 reservations: memory: "128M" cpu: "0.1" minConcurrentTasks: 2Agent 监控和日志
性能监控
PRTCL // YAML
monitoring: agentMetrics: enabled: true metrics: - "response_time" - "token_usage" - "error_rate" - "success_rate" - "user_satisfaction" alertThresholds: response_time: 5000 error_rate: 0.05 token_usage: 10000日志配置
PRTCL // YAML
logging: level: "info" format: "json" outputs: - type: "console" enabled: true - type: "file" enabled: true path: "/var/log/openclaw/agents.log" maxSize: "100M" maxFiles: 10 - type: "elasticsearch" enabled: false url: "http://localhost:9200"审计日志
PRTCL // YAML
audit: enabled: true events: - "agent_created" - "agent_modified" - "agent_deleted" - "agent_invoked" - "skill_called" - "error_occurred" retention: days: 90 compress: trueAgent 安全配置
权限控制
PRTCL // YAML
security: permissions: read: - "file-system" - "database" write: - "file-system" - "database" execute: - "skills" - "tools"
restrictions: forbiddenPaths: - "/etc" - "/root" - "/var/log" maxFileSize: 10485760 # 10MB allowedDomains: - "*.github.com" - "*.stackoverflow.com"数据过滤
PRTCL // YAML
filters: input: enabled: true rules: - type: "pii" action: "redact" - type: "malicious" action: "block" - type: "spam" action: "quarantine"
output: enabled: true rules: - type: "sensitive" action: "encrypt" - type: "confidential" action: "restrict"Agent 测试
单元测试
PRTCL // JAVASCRIPT
describe('Basic Agent', () => { test('should respond to greeting', async () => { const agent = loadAgent('basic-assistant'); const response = await agent.process(' 你好 '); expect(response).toContain(' 你好 '); });
test('should handle unknown queries', async () => { const agent = loadAgent('basic-assistant'); const response = await agent.process('xyz'); expect(response).toContain(' 不确定 '); });});集成测试
PRTCL // JAVASCRIPT
describe('Research Team Integration', () => { test('should complete full research workflow', async () => { const team = loadTeam('research-team'); const result = await team.execute(' 研究 AI 的发展趋势 '); expect(result).toHaveProperty('report'); expect(result).toHaveProperty('insights'); });});Agent 管理命令
Agent 列表
PRTCL // BASH
# 列出所有 Agentdocker compose exec openclaw npm run list-agents
# 列出启用的 Agentdocker compose exec openclaw npm run list-agents --status=enabled
# 列出特定团队docker compose exec openclaw npm run list-agents --team=research-teamAgent 状态
PRTCL // BASH
# 查看 Agent 状态docker compose exec openclaw npm run agent-status --agent=code-reviewer
# 查看性能指标docker compose exec openclaw npm run agent-metrics --agent=code-reviewerAgent 管理
PRTCL // BASH
# 启用 Agentdocker compose exec openclaw npm run enable-agent --agent=code-reviewer
# 禁用 Agentdocker compose exec openclaw npm run disable-agent --agent=code-reviewer
# 重新加载配置docker compose exec openclaw npm run reload-agents
# 删除 Agentdocker compose exec openclaw npm run delete-agent --agent=old-agent故障排查
Agent 无响应
可能原因:
- Agent 配置错误
- 模型 API 不可用
- 资源限制
解决方案:
PRTCL // BASH
# 检查 Agent 配置docker compose exec openclaw npm run validate-agent --agent=code-reviewer
# 查看日志docker compose logs -f openclaw
# 检查资源使用docker stats openclawAgent 路由错误
检查项:
- 路由规则是否正确
- 优先级设置是否合理
- 正则表达式是否匹配
Agent 协作失败
排查步骤:
- 检查 Agent 依赖关系
- 验证通信配置
- 查看团队工作流日志
最佳实践
Agent 设计原则
- 单一职责:每个 Agent 专注于一个领域
- 可复用性:设计通用组件
- 可测试性:编写测试用例
- 可维护性:使用清晰的配置结构
性能优化建议
- 使用缓存减少重复调用
- 批处理相似请求
- 选择合适的模型
- 优化上下文长度
安全建议
- 最小权限原则
- 定期审计配置
- 监控异常行为
- 及时更新依赖
资源链接
- OpenClaw Agent 文档: https://docs.openclaw.ai/agents
- Agent 设计模式: https://patternsofai.io/
- Multi-Agent Systems: https://en.wikipedia.org/wiki/Multi-agent_system
最后更新: 2026-03-12 作者: EchoHaoRan
R P
Rhine Lab Pioneer Division
Auth_Verified: 2026.04.08
Auth_Verified: 2026.04.08
