技能列表

Argues that emotional intelligence becomes strategically critical precisely because of AI -- not despite it -- and provides leaders with practices for developing the soft skills that constitute the human competitive advantage in an AI-saturated economy. Covers empathy, self-awareness, communication beyond technical details, curiosity, proactive problem-solving, trust-building through vulnerability, and coaching teams in EI. Use when an AI project is failing due to poor leadership connection, whe

|

|

Fetches AI news from smol.ai RSS. Use when user asks about AI news or daily tech updates.

AI 成本计算器 - 对比各大模型成本，优化 API 支出。适合：AI 应用开发者、成本敏感用户。

Equips leaders to build flat, participative communication cultures that enable successful AI adoption by bridging technical and business teams, democratising data, and establishing feedback loops. Covers the symphony conductor model, soliciting expert feedback, removing bureaucratic obstacles, and building shared responsibility. Use when AI projects fail due to communication breakdowns, when data scientists and business leaders operate in silos, when employees lack channels to provide AI feedbac

一站式AI编程工具分析技能包，支持Cursor、Claude Code、Devin、Windsurf等35+工具的深度分析、对比选型、Agent设计参考和提示词工程。封装了11个技能，覆盖 35+AI编程工具。当用户想要分析、学习、对比AI编程工具，或需要设计AI Agent系统、编写高效提示词时使用。触发指令：/ai-tools、/aitools、@ai-coding-tools-full-suite。

AI code generator using Plan-and-Solve + ReAct for generating complete, runnable code from requirements and specifications.

Design CLI tools as local APIs for AI agents. TTY detection, --json output, stderr/stdout separation, exit codes. | 为 AI 设计 CLI 工具的规范：TTY 检测、JSON 输出、stderr/stdout 分离、退出码。

AI CLI 产品的工程架构与迭代策略。当需要设计、开发、或迭代 AI 命令行工具类产品时使用，包括：功能模块化设计、渐进式版本规划、Feature Flag 机制、多后端适配、权限系统、Hook 系统、上下文管理、会话恢复、诊断工具、审计追责、可观测性、信任链设计、状态机思维等。触发场景：构建 AI CLI、规划产品路线图、设计架构方案、分析竞品工程实现。

智能分析用户需求并推荐最适合的ClawHub技能，提供实时技能搜索、安全评估和使用建议。

Makes the strategic and moral case for AI augmentation over pure automation, providing leaders with frameworks for job redesign, creativity-driven AI deployment, and long-term workforce investment. Draws on the centaur model from chess and case studies across industries to demonstrate that human-AI collaboration outperforms either alone. Use when deciding between automating jobs and redesigning them, when AI adoption is eroding workforce skills, when boards pressure for automation-driven cost cu