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curiositech/windags-skills

Límites de velocidad basados en token bucket, ventana deslizante y Redis para proteger APIs. Actívalo en: limitación de velocidad, estrangulamiento, token bucket, ventana deslizante, abuso de API, protección DDoS, gestión de cuotas. NO para: configuración de pasarela API (usa api-gateway-reverse-proxy-expert), almacenamiento en caché (usa cache-strategy-invalidation-expert).

¿Qué es windags-skills?

Esta habilidad te permite implementar limitación de velocidad justa y eficiente en APIs utilizando los algoritmos de token bucket, ventana deslizante y ventana fija, respaldados por contadores distribuidos basados en Redis. Es útil porque protege tus APIs contra abusos, ataques DDoS y sobrecargas, gestionando cuotas por clave de API, IP o nivel de usuario. Funciona en Node.js (con librerías como rate-limiter-flexible), Python, Go o cualquiera que pueda usar Redis, y se integra con pasarelas como Kong, Nginx y Traefik. La habilidad incluye scripts Lua para operaciones atómicas, cabeceras estándar del IETF y arquitecturas multinivel para planes free/pro/enterprise, evitando antipatrones como límites solo en memoria o falta de la cabecera Retry-After.

Compatible con~Claude Code~Codex CLI~Cursor
npx skills add https://github.com/curiositech/windags-skills/tree/HEAD/skills/api-rate-limiting-throttling-expert

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Documentación

Experto en Limitación de Velocidad y Estrangulamiento de API

Implementa limitación de velocidad justa y eficiente usando los algoritmos de token bucket, ventana deslizante y ventana fija con contadores distribuidos respaldados por Redis.

Disparadores de Activación

Actívalo en: "limitación de velocidad", "estrangulamiento", "token bucket", "ventana deslizante", "abuso de API", "protección DDoS", "gestión de cuotas", "429 Demasiadas Solicitudes", "límites de solicitud"

NO para: Configuración de pasarela API → api-gateway-reverse-proxy-expert | Estrategias de caché → cache-strategy-invalidation-expert | Reglas de WAF/firewall → habilidad de seguridad relevante

Inicio Rápido

  1. Define límites — solicitudes/minuto por clave de API, IP o nivel de usuario
  2. Elige algoritmo — registro de ventana deslizante (preciso), token bucket (ráfagas), ventana fija (simple)
  3. Usa Redis — operaciones atómicas con MULTI/EXEC o scripts Lua para limitación distribuida
  4. Devuelve cabeceras correctas — X-RateLimit-Limit, X-RateLimit-Remaining, Retry-After
  5. Diferencia niveles — free/pro/enterprise obtienen límites distintos

Capacidades Principales

DominioTecnologías
AlgoritmosToken bucket, registro de ventana deslizante, contador de ventana deslizante, ventana fija
AlmacenamientoRedis 7.4+, Valkey, DragonflyDB, en memoria (nodo único)
Libreríasrate-limiter-flexible, @upstash/ratelimit, express-rate-limit
Plugins de PasarelaKong rate-limiting, Nginx limit_req, Traefik ratelimit
EstándaresRFC 6585 (429), Cabeceras RateLimit (draft-ietf-httpapi-ratelimit)

Patrones de Arquitectura

Contador de Ventana Deslizante (Redis Lua)

-- Script Lua de Redis: limitador de ventana deslizante
-- KEYS[1] = clave de límite
-- ARGV[1] = tamaño de ventana (segundos)
-- ARGV[2] = solicitudes máximas
-- ARGV[3] = marca de tiempo actual

local key = KEYS[1]
local window = tonumber(ARGV[1])
local limit = tonumber(ARGV[2])
local now = tonumber(ARGV[3])

-- Eliminar entradas caducadas
redis.call('ZREMRANGEBYSCORE', key, 0, now - window)

-- Contar ventana actual
local count = redis.call('ZCARD', key)

if count < limit then
  redis.call('ZADD', key, now, now .. '-' .. math.random(1000000))
  redis.call('EXPIRE', key, window)
  return {1, limit - count - 1}  -- permitido, restante
else
  return {0, 0}  -- denegado, 0 restante
end

Limitación Multinivel

Solicitud → Límite de IP (100/min)
              │ pasar
              ↓
         Verificación de Auth → Límite de clave de API (basado en nivel)
              │           Free:  60/min
              │           Pro:   600/min
              │           Enterprise: 6000/min
              ↓ pasar
         Límite de Endpoint (por ruta)
              │   POST /subir: 10/min
              │   GET /buscar:  120/min
              ↓ pasar
         Procesar Solicitud

Cabeceras de Respuesta (Borrador Estándar IETF)

// Middleware: adjuntar cabeceras de límite
function cabecerasLimite(limite: number, restante: number, restablecerEn: number) {
  return {
    'RateLimit-Limit': limite.toString(),
    'RateLimit-Remaining': Math.max(0, restante).toString(),
    'RateLimit-Reset': Math.ceil((restablecerEn - Date.now()) / 1000).toString(),
  };
}

// En respuesta 429:
res.status(429).set({
  ...cabecerasLimite(limite, 0, restablecerEn),
  'Retry-After': Math.ceil((restablecerEn - Date.now()) / 1000).toString(),
}).json({ error: 'Demasiadas Solicitudes', reintentarDespues: restablecerEn });

Antipatrones

  1. Contadores en memoria en sistemas distribuidos — los límites deben compartirse entre instancias; usa Redis o equivalente
  2. Falta de cabecera Retry-After — las respuestas 429 sin Retry-After obligan a los clientes a adivinar, provocando avalanchas
  3. Limitación solo por IP — los límites de IP ignoran el abuso autenticado y castigan IPs compartidas (NAT, VPN); combínalo con límites por clave de API
  4. Corte brusco sin ráfaga — token bucket permite pequeñas ráfagas manteniendo la tasa media; la ventana fija pura es demasiado rígida
  5. Sin límite en APIs internas — un servicio interno que se comporte mal puede cascada-fallar tu base de datos; siempre limita

Lista de Verificación de Calidad

  • Los límites usan almacenamiento distribuido (Redis/Valkey), no en memoria
  • Cabeceras RateLimit-Limit, RateLimit-Remaining, RateLimit-Reset en cada respuesta
  • Cabecera Retry-After en respuestas 429
  • Límites diferentes por nivel de autenticación (free/pro/enterprise)
  • Límites por endpoint para operaciones costosas (subidas, búsquedas)
  • Script Lua o pipeline atómico para incremento de contador (sin condiciones de carrera)
  • Las claves de límite incluyen tanto identidad (clave API) como ámbito (endpoint)
  • El panel de monitoreo muestra aciertos, denegaciones y principales consumidores de límites
  • Degradación gradual: poner en cola o ralentizar en lugar de rechazar tajantemente cuando sea posible

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

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).

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

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

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