Communitygithub.com

代理创建器

用于创建自定义代理、技能和MCP集成的元代理。专注于代理设计、MCP开发、技能架构和快速原型设计。适用于“创建代理”、“新技能”、“MCP服务器”、“自定义工具”、“代理设计”等场景。不适用于使用现有代理(请直接调用)、通用编码(请使用特定语言技能)或基础设施设置(请使用部署工程师)。

代理创建器 是什么?

Agent Creator 是一个高级元代理,专门用于设计和构建新的自定义 AI 代理、技能和 MCP(模型上下文协议)集成。它不仅能将抽象需求转化为功能完备、文档齐全的代理系统,还提供了一套完整的快速原型工作流,帮助开发者在约 45 分钟内打造生产就绪的代理。该技能支持多种代理模板(如技术专家、创意/设计、编排器),并涵盖了从角色设计、知识编码、MCP 服务器搭建到质量检查的完整流程。它适用于创建领域专家代理、设计技能架构和快速验证 AI 能力,但不适用于直接调用现有代理、通用编程或基础设施部署。其核心设计理念是避免成为知识库转储,而是构建具有明确角色、实用指导和真实用例的专家系统。

兼容平台✓Claude Code~Codex CLI~Cursor
npx skills add https://github.com/curiositech/windags-skills/tree/HEAD/skills/agent-creator

在你喜欢的 AI 中提问

打开一个已预加载此 Agent Skill 的新对话。

文档

代理创建器 是做什么的?

元代理,专门用于创建新的自定义代理、技能和 MCP 集成。将需求转化为功能完备、文档齐全的代理系统。

快速开始

用户:"创建一个用于数据库优化的代理"

代理创建器:
1. 分析需求(领域、用户、问题、范围)
2. 设计角色(高级 DBA,20 年经验)
3. 映射能力(EXPLAIN 分析、索引、查询重写)
4. 选择模板(技术专家)
5. 编码知识(反模式、技术、示例)
6. 添加 MCP 工具(可选:SQL 解析器)
7. 记录使用方法和限制

结果:约 45 分钟即可获得生产就绪的代理

核心能力

1. 代理设计与架构

  • 角色开发,具有鲜明的话语风格
  • 技能定义与范围管理
  • 交互模式设计
  • 知识编码以优化检索

2. MCP 集成

  • 协议理解与服务器开发
  • 资源管理与 API 设计
  • 持久化代理的状态管理

3. 技能框架设计

  • 渐进式信息呈现(轻量元数据,按需提供细节)
  • 可组合性与模块化
  • 清晰的文档

代理模板

模板最佳用途关键要素
技术专家领域专家问题解决框架、代码示例、最佳实践
创意/设计创意角色设计理念、创意流程、质量标准
编排器协调任务委托策略、集成模式、质量保证

快速原型工作流

步骤时间活动
1. 理解需求2 分钟缺少什么能力?
2. 设计角色3 分钟哪位专家能够解决此问题?
3. 映射知识10 分钟他们需要了解什么?
4. 创建结构5 分钟按模板组织
5. 添加示例10 分钟具体、可运行的代码
6. 编写文档5 分钟如何使用
7. 测试与改进10 分钟用查询验证

总计:约 45 分钟即可获得高质量的代理

MCP 服务器创建

官方包:

  • @modelcontextprotocol/sdk - 核心 TypeScript SDK
  • @modelcontextprotocol/create-server - 脚手架新服务器
  • @modelcontextprotocol/inspector - 测试和调试

创建步骤:

  1. 定义能力(输入、输出、目的)
  2. 设计接口(清晰的工具模式)
  3. 实现核心逻辑
  4. 打包为 MCP 服务器

质量检查清单

专业性

  • 清晰的领域边界
  • 具体、可操作的指导
  • 真实世界的示例
  • 涵盖常见陷阱

可用性

  • 明确的使命陈述
  • 易于浏览的结构
  • 具体的代码示例

集成

  • 可独立运行
  • 可与其他代理组合
  • 清晰的输入/输出格式

何时使用

适用于:

  • 创建新的领域专家代理
  • 为自定义能力构建 MCP 服务器
  • 设计技能架构
  • 快速原型化 AI 能力

不适用于:

  • 使用现有代理(请直接调用)
  • 通用编码任务(请使用特定语言技能)
  • 基础设施设置(请使用部署工程师)
  • 修改 Claude 的核心行为

反模式

反模式:知识库转储

表现:将整个文档粘贴到代理中 错误原因:信息过载、检索效果差、上下文臃肿 替代方案:精选关键知识,使用渐进式信息呈现

反模式:模糊角色

表现:"你是一位专家助手" 错误原因:缺乏个性,输出千篇一律 替代方案:指定具体角色、工作年限、沟通风格

反模式:范围缺失

表现:试图包揽一切的代理 错误原因:样样通,样样松 替代方案:设定清晰边界,并提供重定向建议

反模式:缺少示例

表现:只有抽象描述,没有代码 错误原因:用户看不到如何应用指导 替代方案:为核心模式提供具体、可运行的示例

参考文件

  • references/agent-templates.md - 技术、创意、编排器模板
  • references/mcp-integration.md - MCP 服务器创建模式、SDK 使用
  • references/creation-process.md - 端到端工作流、质量检查清单

核心洞察:优秀的代理不是知识库转储——它们是经过深思熟虑设计的专家系统,具有个性、实用指导和真实世界的适用性。

配合使用:skill-coach(质量审查)| skill-documentarian(文档生成)| orchestrator(多代理设计)

Individual skills in this repo

This repo contains 20 individual skills — each has its own dedicated page.

curiositech/windags-skills

Expert in 2000s-era music visualization (Milkdrop, AVS, Geiss) and modern WebGL implementations. Specializes in Butterchurn integration, Web Audio API AnalyserNode FFT data, GLSL shaders for audio-reactive visuals, and psychedelic generative art. Activate on "Milkdrop", "music visualization", "WebGL visualizer", "Butterchurn", "audio reactive", "FFT visualization", "spectrum analyzer". NOT for simple bar charts/waveforms (use basic canvas), video editing, or non-audio visuals.

curiositech/windags-skills

Expert legal research agent for finding and scraping expungement data state by state. Knows authoritative sources, URL patterns, Firecrawl configuration, and 2026 legal landscape.

curiositech/windags-skills

Expert in 3D computer vision labeling tools, workflows, and AI-assisted annotation for LiDAR, point clouds, and sensor fusion. Covers SAM4D/Point-SAM, human-in-the-loop architectures, and vertical-specific training strategies. Activate on '3D labeling', 'point cloud annotation', 'LiDAR labeling', 'SAM 3D', 'SAM4D', 'sensor fusion annotation', '3D bounding box', 'semantic segmentation point cloud'. NOT for 2D image labeling (use clip-aware-embeddings), general ML training (use ml-engineer), video annotation without 3D (use computer-vision-pipeline), or VLM prompt engineering (use prompt-engineer).

curiositech/windags-skills

Implement WCAG 2.2 AA/AAA compliance with automated testing, keyboard navigation, screen reader support, and focus management. Activate on: accessibility audit, WCAG compliance, keyboard navigation, screen reader, aria attributes, axe-core, focus trap. NOT for: design-level accessibility review (use design-accessibility-auditor), color contrast only (use css-in-js-architect).

curiositech/windags-skills

Time-blind friendly planning, executive function support, and daily structure for ADHD brains. Specializes in realistic time estimation, dopamine-aware task design, and building systems that actually work for neurodivergent minds.

curiositech/windags-skills

Designs digital experiences for ADHD brains using neuroscience research and UX principles. Expert in reducing cognitive load, time blindness solutions, dopamine-driven engagement, and compassionate design patterns. Activate on 'ADHD design', 'cognitive load', 'accessibility', 'neurodivergent UX', 'time blindness', 'dopamine-driven', 'executive function'. NOT for general accessibility (WCAG only), neurotypical UX design, or simple UI styling without ADHD context.

curiositech/windags-skills

>- Apply crisis decision-making research to agent routing, uncertainty triage, and coordination failure analysis in time-pressured systems. Use when diagnosing handoff failures, analytical paralysis, or expert judgment under incomplete information. NOT for routine coding, simple CRUD design, or static single-agent tasks with complete information.

curiositech/windags-skills

Extend and modify the admin dashboard, developer portal, and operations console. Use when adding new admin tabs, metrics, monitoring features, or internal tools. Activates for dashboard development, analytics, user management, and internal tooling.

curiositech/windags-skills

Conversation patterns and interaction protocols for multi-agent systems. Covers request/response, pub/sub, blackboard, delegation chains, debate, critique, consensus, fan-out/fan-in, supervisor-worker, and peer negotiation. Deep analysis of AutoGen conversation patterns, CrewAI delegation, LangGraph state passing, and FIPA-ACL performatives. Teaches how to design what agents say to each other and in what order. Activate on: "agent conversation", "agent protocol", "multi-agent debate", "agent delegation", "supervisor worker pattern", "agent voting", "consensus protocol", "fan-out fan-in", "agent negotiation", "blackboard pattern", "agent dialogue", "conversation topology", "agent handoff". NOT for: wire format or serialization (use agent-interchange-formats), orchestration infrastructure (use agentic-infrastructure-2026), single agent behavior (use agentic-patterns).

curiositech/windags-skills

AI-powered calendar management and agent-based scheduling coordination. Covers calendar APIs (Google Calendar, CalDAV/iCal), AI scheduling assistants (Reclaim, Clockwise, Motion, Cal.com), building custom calendar agents with MCP, multi-calendar merging, timezone management, focus block protection, meeting fatigue detection, and agent-to-agent meeting negotiation protocols. Activate on: "calendar agent", "AI scheduling", "calendar coordination", "meeting scheduling", "calendar API", "focus time protection", "calendar optimization", "Google Calendar MCP", "Reclaim", "Clockwise", "Motion", "Cal.com", "smart scheduling", "calendar-aware agent", "timezone scheduling", "agent negotiation meetings". NOT for: manual calendar UI component design (use form-validation-architect), project management scheduling or Gantt charts (use project-management-guru-adhd), general time-tracking or pomodoro apps (use adhd-daily-planner for time-awareness), building the agent itself from scratch (use agent-creator).

curiositech/windags-skills

Build and adopt production AI agent infrastructure in 2026. Covers framework selection (LangGraph, CrewAI, AutoGen, MCP), orchestration patterns, evaluation, observability, memory systems, and tool use. Also covers the SOCIAL dimension: how to sell agent infrastructure internally, change management, measuring ROI, building trust in autonomous systems, and scaling adoption across teams. Activate on: "agent infrastructure", "agent framework comparison", "which agent framework", "sell AI tools internally", "agent adoption", "agent observability", "agent evaluation", "MCP architecture", "agentic mesh", "enterprise AI agents", "AI change management", "agent ROI". NOT for: building specific agents (use ai-engineer), designing agent behavior patterns (use agentic-patterns), prompt tuning (use prompt-engineer).

curiositech/windags-skills

Fundamental patterns for effective agentic behavior. Teaches decomposition, tool orchestration, error recovery, context management, quality self-assessment, and knowing when to stop. Model-agnostic principles that make any agent more effective regardless of domain. Activate on: "how should I structure this agent", "agentic workflow", "agent patterns", "multi-step task", "tool orchestration", "/agentic-patterns", "decompose this", "agent best practices", "chain of actions", "when should the agent stop", "agent loop design". NOT for: creating agent infrastructure (use agent-creator), building DAGs (use windags-architect), specific tool implementation.

curiositech/windags-skills

Automated discovery and matching of agent skills for dynamic task routing and capability assessment

curiositech/windags-skills

Cryptographic security for agentic systems — zero-trust agent networking, signed message envelopes (JWS/JWE), capability-based security (ocaps), Merkle tree audit trails, WASM sandboxing, and formal verification. Covers CLI dev tool security, mTLS between agents, permission boundaries (least privilege for AI agents), and supply chain security for skills/plugins. Activate on: "agent security", "zero trust agents", "secure agent communication", "capability-based security", "ocap", "signed messages between agents", "agent audit trail", "sandbox agent execution", "agent permissions", "mTLS agents", "cryptographic verification", "agent supply chain", "OWASP agentic", "prove agent did X", "tamper-proof agent logs". NOT for: application-level SAST scanning (use security-auditor), network firewall rules (use infrastructure), SOC2/HIPAA compliance (organizational), or prompt injection defense (use prompt-engineer).

curiositech/windags-skills

Data structures and serialization formats for agent-to-agent communication. Covers message envelopes, structured output schemas, capability declarations, task handoff payloads, error/retry signaling, and context windows as data structures. Deep comparison of A2A protocol, MCP, OpenAI function calling, and LangChain message types. Teaches when to use rigid schemas vs free-form with validation, typed vs untyped, streaming vs batch. Activate on: "agent message format", "agent communication schema", "agent-to-agent protocol", "A2A protocol", "MCP message format", "structured output for agents", "agent interop", "interchange format", "agent serialization", "task handoff format", "capability declaration". NOT for: what agents say to each other (use agent-conversation-protocols), orchestration topology (use multi-agent-coordination), building agent infrastructure (use agentic-infrastructure-2026).

curiositech/windags-skills

Logic-based agent programming language implementing BDI architecture for practical autonomous agent development

curiositech/windags-skills

>- Design AgentSpeak(L)-style BDI agents with context-guarded plans, selection functions, and intention stacks. Use for interruptible autonomy, agent policy, and multi-agent orchestration in dynamic environments. NOT for simple rule engines, static planners, or centralized workflows.

curiositech/windags-skills

Foundational concurrent computation model where actors communicate exclusively through asynchronous message passing

curiositech/windags-skills

Build production-ready LLM applications, advanced RAG systems, and intelligent agents. Implements vector search, multimodal AI, agent orchestration, and enterprise AI integrations. Use PROACTIVELY for LLM features, chatbots, AI agents, or AI-powered applications.

curiositech/windags-skills

license: Apache-2.0 NOT for unrelated tasks outside this domain.

相关技能