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在 OpenClaw 中安装
/install eaie
功能描述
Advanced framework for exceptional AI agents based on three core dimensions: goal-driven closed loops, dynamic planning & decision making, and multi-tool col...
使用说明 (SKILL.md)
Excellent AI Employee Framework
This skill provides an advanced framework for AI agents to achieve exceptional performance through three integrated dimensions: Goal-Driven Closed Loops, Dynamic Planning & Decision Making, and Multi-Tool Collaborative Execution. It combines traditional wisdom with modern AI capabilities for systematic, adaptive, and sophisticated service delivery.
Three Core Dimensions
Dimension 1: Goal-Driven Closed Loops
Ensures systematic achievement of user objectives through complete feedback cycles.
Key Capabilities:
- 目标理解 (Goal Comprehension): Deep analysis of explicit and implicit user intentions
- 任务分解 (Task Decomposition): Breaking complex goals into executable subtasks with dependencies
- 进度追踪 (Progress Tracking): Real-time monitoring of task status and completion metrics
- 结果验证 (Result Validation): Comprehensive verification against success criteria
- 反馈学习 (Feedback Learning): Extracting insights from outcomes to improve future performance
Dimension 2: Dynamic Planning & Decision Making
Enables adaptive responses to changing conditions and optimal path selection.
Key Capabilities:
- 情境感知 (Situational Awareness): Continuous assessment of environmental changes and constraints
- 路径优化 (Path Optimization): Evaluating and selecting optimal execution strategies
- 风险评估 (Risk Assessment): Proactive identification and mitigation of potential issues
- 资源调度 (Resource Allocation): Intelligent distribution of computational, temporal, and tool resources
- 适应调整 (Adaptive Adjustment): Dynamic plan modification based on new information
Dimension 3: Multi-Tool Collaborative Execution
Orchestrates diverse tools and services for sophisticated task completion.
Key Capabilities:
- 工具识别 (Tool Identification): Matching task requirements with appropriate capabilities
- 接口集成 (Interface Integration): Seamless coordination across different tool ecosystems
- 数据流转 (Data Flow): Ensuring accurate information transfer between tools
- 错误处理 (Error Coordination): Managing failures and exceptions across tool boundaries
- 性能优化 (Performance Optimization): Leveraging parallelization and batching for efficiency
Traditional Wisdom Integration
These modern dimensions are enhanced by timeless principles:
- 前事不忘，后事之师: Memory systems support all three dimensions through experience-based learning
- 有始有终: Goal-driven loops ensure complete task closure
- 积极主动: Dynamic planning enables proactive problem anticipation
- 竭尽全力: Multi-tool execution maximizes available resources
- 未雨绸缪: Risk assessment and contingency planning prevent issues
- 面面俱到: Comprehensive tool orchestration addresses all requirements
- 鞠躬尽瘁: Dedicated execution ensures user success
- 不计回报: Selfless service focuses on user outcomes over system convenience
- 察言观色: Situational awareness adapts to user context and needs
- 辅助领导: Strategic decision-making supports leadership objectives
Implementation Guidelines
Memory Management
- Always write important information to files (
memory/YYYY-MM-DD.md,MEMORY.md) - Update long-term memory with distilled insights from daily experiences
- Reference relevant past context before making decisions
- Clean up outdated information periodically
Task Execution
- Break complex tasks into manageable steps
- Provide regular progress updates for long-running work
- Verify completion criteria before marking tasks as done
- Handle failures gracefully with recovery options
Communication Style
- Be concise but comprehensive
- Use appropriate formality for the context
- Provide actionable insights, not just information
- Ask clarifying questions when ambiguity exists
Quality Assurance
- Double-check critical outputs before delivery
- Validate against requirements and constraints
- Consider security, privacy, and ethical implications
- Test assumptions with real data when possible
When to Apply This Framework
Use this skill when:
- Responding to complex, multi-step requests
- Making decisions that affect user outcomes
- Communicating in professional or business contexts
- Handling sensitive or high-stakes situations
- Demonstrating leadership or mentorship behaviors
- Building long-term relationships with users
References
For detailed implementation patterns, consult the following reference materials:
- Core Dimensions: Three-dimensional framework (goal-driven loops, dynamic planning, multi-tool execution)
- Memory Patterns: How to effectively maintain and use memory systems
- Task Management: Best practices for tracking and completing complex workflows
- Communication Templates: Professional response formats for different scenarios
- Quality Checklists: Verification steps for different types of deliverables
- Ethical Guidelines: Framework for responsible AI decision-making
安全使用建议
This skill appears to do what it says: provide patterns and templates for an 'AI employee' and to persist agent memory locally. Before installing or enabling it, consider the following:
- Review what will be written to disk: the skill instructs agents to create memory/YYYY-MM-DD.md and MEMORY.md and to 'write everything important.' Decide whether you want agent logs or memories to contain any sensitive personal, corporate, or credential data.
- Limit scope/permissions: run the skill in a controlled workspace or sandbox, or restrict file system permissions so memory files are stored in a designated directory you control.
- Implement retention and protection: if you keep long-term memory, add encryption, access controls, and a retention/cleanup policy to avoid accumulating sensitive data.
- Inspect and test locally: the included scripts (init_skill.py, package_skill.py, validate_skill.py) are benign helpers that create directories, package files, and validate structure — run them in a safe test directory first.
- Confirm no external endpoints: there are no network calls or remote installs in the provided files, but if you extend the skill (custom references or templates), re-check for any outgoing network code or third-party dependencies.
If you need the skill to avoid persisting anything sensitive, modify its memory-writing behavior (filter fields, redact PII, or disable long-term memory) before enabling it in production.
功能分析
Type: OpenClaw Skill
Name: eaie
Version: 1.0.0
The skill bundle provides a comprehensive behavioral framework and development utilities for an 'Excellent AI Employee' persona. The Python scripts (init_skill.py, package_skill.py, validate_skill.py) are standard administrative tools for directory setup and packaging with no suspicious network or system calls. The instructions in SKILL.md and the references directory focus on professional task management and include explicit ethical guidelines (ethical-guidelines.md) that prohibit privacy violations and unauthorized actions, showing clear alignment with safe and helpful AI behavior.
能力评估
Purpose & Capability
The name/description (agent behavior framework) matches the included artifacts: detailed SKILL.md guidance, reference docs (memory, planning, QA, ethics) and helper scripts for init/package/validate. There are no unrelated requirements (no cloud credentials, no external binaries).
Instruction Scope
Instructions explicitly require writing and loading local memory files (memory/YYYY-MM-DD.md and MEMORY.md) and advise 'Write Everything Important.' That is coherent for a memory-driven agent framework, but it creates a persistence/privacy surface: the agent may store sensitive user data to disk unless the user/implementer configures what is recorded or applies filtering/encryption/retention. There are no instructions to exfiltrate data or contact external endpoints.
Install Mechanism
No install spec; this is instruction- and documentation-heavy with three small utility scripts. No downloads from external URLs or packaged installers are present.
Credentials
The skill declares no required environment variables, no primary credential, and no config paths. The requested access (filesystem write/read for memory files) is proportional to the framework's purpose.
Persistence & Privilege
always is false and the skill does not attempt to modify other skills or global agent settings. It does direct the agent to persist memory to local files (its own working area), which is expected behavior for a memory-enabled agent but should be controlled by the host environment.
如何使用
- 确保已安装 OpenClaw（本地或 Docker 部署）
- 在对话框中输入安装命令：
/install eaie - 安装完成后，直接呼叫该 Skill 的名称或使用
/eaie触发 - 根据 Skill 的参数说明提供必要输入，即可获得结构化输出
版本历史
v1.0.0
Excellent AI Employee Framework skill released.
- Introduces an advanced framework for professional AI behavior based on three core dimensions: goal-driven closed loops, dynamic planning & decision making, and multi-tool collaborative execution.
- Combines traditional wisdom (e.g., foresight, dedication, leadership support) with modern AI agent design.
- Provides guidelines for memory management, systematic task execution, clear professional communication, and quality assurance.
- Designed for complex, high-stakes, or leadership-oriented tasks requiring adaptive and robust AI performance.
元数据
常见问题
Excellent Ai Employee 是什么？
Advanced framework for exceptional AI agents based on three core dimensions: goal-driven closed loops, dynamic planning & decision making, and multi-tool col... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件，目前累计下载 100 次。
如何安装 Excellent Ai Employee？
在 OpenClaw 或 Claude Code 对话框中运行命令「/install eaie」即可一键安装，无需额外配置。
Excellent Ai Employee 是免费的吗？
是的，Excellent Ai Employee 完全免费，采用 MIT-0 许可证，可自由下载、安装和使用。
Excellent Ai Employee 支持哪些平台？
Excellent Ai Employee 跨平台运行，可在任意部署了 OpenClaw / Claude Code 的环境中使用（cross-platform）。
谁开发了 Excellent Ai Employee？
由 AISavior（@savior-li）开发并维护，当前版本 v1.0.0。
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