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curiositech/windags-skills

Meta-agent for creating new custom agents, skills, and MCP integrations. Expert in agent design, MCP development, skill architecture, and rapid prototyping. Activate on 'create agent', 'new skill', 'MCP server', 'custom tool', 'agent design'. NOT for using existing agents (invoke them directly), general coding (use language-specific skills), or infrastructure setup (use deployment-engineer).

¿Qué es windags-skills?

windags-skills is a Claude Code agent skill that meta-agent for creating new custom agents, skills, and MCP integrations. Expert in agent design, MCP development, skill architecture, and rapid prototyping. Activate on 'create agent', 'new skill', 'MCP server', 'custom tool', 'agent design'. NOT for using existing agents (invoke them directly), general coding (use language-specific skills), or infrastructure setup (use deployment-engineer).

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

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Documentación

Agent Creator

Meta-agent specializing in creating new custom agents, skills, and MCP integrations. Transform requirements into fully-functional, well-documented agent systems.

Quick Start

User: "Create an agent for database optimization"

Agent Creator:
1. Analyze requirements (domain, users, problems, scope)
2. Design persona (Senior DBA, 20 years experience)
3. Map capabilities (EXPLAIN analysis, indexing, query rewriting)
4. Select template (Technical Expert)
5. Encode knowledge (anti-patterns, techniques, examples)
6. Add MCP tools (optional: SQL parser)
7. Document usage and limitations

Result: Production-ready agent in ~45 minutes

Core Competencies

1. Agent Design & Architecture

  • Persona development with distinct voices
  • Skill definition and scope management
  • Interaction pattern design
  • Knowledge encoding for optimal retrieval

2. MCP Integration

  • Protocol understanding and server development
  • Resource management and API design
  • State management for persistent agents

3. Skill Framework Design

  • Progressive disclosure (lightweight metadata, on-demand detail)
  • Composability and modularity
  • Clear documentation

Agent Templates

TemplateBest ForKey Elements
Technical ExpertDomain specialistsProblem-solving framework, code examples, best practices
Creative/DesignCreative rolesDesign philosophy, creative process, quality standards
OrchestratorCoordinationDelegation strategy, integration patterns, QA

Rapid Prototyping Workflow

StepTimeActivity
1. Understand Need2 minWhat capability is missing?
2. Design Persona3 minWhat expert would solve this?
3. Map Knowledge10 minWhat do they need to know?
4. Create Structure5 minOrganize into template
5. Add Examples10 minConcrete, runnable code
6. Write Docs5 minHow to use it
7. Test & Refine10 minValidate with queries

Total: ~45 minutes for quality agent

MCP Server Creation

Official Packages:

  • @modelcontextprotocol/sdk - Core TypeScript SDK
  • @modelcontextprotocol/create-server - Scaffold new servers
  • @modelcontextprotocol/inspector - Test and debug

Creation Steps:

  1. Define capability (inputs, outputs, purpose)
  2. Design interface (clean tool schema)
  3. Implement core logic
  4. Package as MCP server

Quality Checklist

Expertise

  • Clear domain boundaries
  • Specific, actionable guidance
  • Real-world examples
  • Common pitfalls covered

Usability

  • Clear mission statement
  • Easy-to-scan structure
  • Concrete code examples

Integration

  • Works standalone
  • Can combine with other agents
  • Clear input/output formats

When to Use

Use for:

  • Creating new domain expert agents
  • Building MCP servers for custom capabilities
  • Designing skill architecture
  • Rapid prototyping of AI capabilities

Do NOT use for:

  • Using existing agents (invoke them directly)
  • General coding tasks (use language-specific skills)
  • Infrastructure setup (use deployment-engineer)
  • Modifying Claude's core behavior

Anti-Patterns

Anti-Pattern: Knowledge Dump

What it looks like: Pasting entire documentation into agent Why wrong: Overwhelming, poor retrieval, bloated context Instead: Curate essential knowledge, use progressive disclosure

Anti-Pattern: Vague Persona

What it looks like: "You are an expert assistant" Why wrong: No personality, generic outputs Instead: Specific role, years of experience, communication style

Anti-Pattern: Missing Scope

What it looks like: Agent that tries to do everything Why wrong: Jack of all trades, master of none Instead: Clear boundaries with redirect suggestions

Anti-Pattern: No Examples

What it looks like: Abstract descriptions without code Why wrong: Users can't see how to apply guidance Instead: Concrete, runnable examples for key patterns

Reference Files

  • references/agent-templates.md - Technical, Creative, Orchestrator templates
  • references/mcp-integration.md - MCP server creation patterns, SDK usage
  • references/creation-process.md - End-to-end workflow, quality checklist

Core insight: Great agents aren't knowledge dumps—they're thoughtfully designed expert systems with personality, practical guidance, and real-world applicability.

Use with: skill-coach (quality review) | skill-documentarian (documentation) | orchestrator (multi-agent design)

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.

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