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Crisp - Atención al cliente en vivo

Agrega chat en vivo y atención al cliente con Crisp. Se usa cuando un usuario pide añadir un widget de chat, implementar atención al cliente en vivo, configurar un sistema de tickets, crear una base de conocimientos o añadir un chatbot a un sitio web.

¿Qué es Crisp - Atención al cliente en vivo?

Crisp es una plataforma integral de mensajería para clientes: widget de chat en vivo, bandeja compartida, base de conocimientos, chatbot y CRM. Esta skill permite integrar Crisp en aplicaciones web y React/Next.js de forma sencilla, con solo añadir un script o un componente. También incluye ejemplos de integración vía API para enviar mensajes y gestionar conversaciones desde el backend. Es útil para desarrolladores que buscan una solución rápida y escalable de atención al cliente. Soporta desde un tier gratuito (2 operadores, conversaciones ilimitadas) hasta planes profesionales con chatbot automatizado. La skill proporciona instrucciones paso a paso, código de ejemplo y guías de uso de datos de sesión para enriquecer el contexto del agente.

Compatible con~Claude Code~Codex CLI~Cursor
npx skills add https://github.com/TerminalSkills/skills/tree/HEAD/skills/crisp

Preguntar en tu IA favorita

Abre un nuevo chat con esta habilidad de agente ya precargada.

Documentación

Crisp

Resumen

Crisp es una plataforma integral de mensajería para clientes: widget de chat en vivo, bandeja compartida, base de conocimientos, chatbot y CRM. El nivel gratuito permite 2 operadores con conversaciones ilimitadas.

Instrucciones

Paso 1: Añadir el widget de chat

<!-- Añade a tu sitio web — instalación básica -->
<script type="text/javascript">
  window.$crisp=[];window.CRISP_WEBSITE_ID="TU_ID_DE_SITIO";
  (function(){d=document;s=d.createElement("script");
  s.src="https://client.crisp.chat/l.js";
  s.async=1;d.getElementsByTagName("head")[0].appendChild(s);})();
</script>

Paso 2: Integración con React

// components/CrispChat.tsx — Crisp en React/Next.js
'use client'
import { useEffect } from 'react'

export function CrispChat() {
  useEffect(() => {
    window.$crisp = []
    window.CRISP_WEBSITE_ID = process.env.NEXT_PUBLIC_CRISP_ID!
    const s = document.createElement('script')
    s.src = 'https://client.crisp.chat/l.js'
    s.async = true
    document.head.appendChild(s)
  }, [])
  return null
}

// Establece datos del usuario cuando inicia sesión
window.$crisp.push(['set', 'user:email', ['[email protected]']])
window.$crisp.push(['set', 'user:nickname', ['John']])
window.$crisp.push(['set', 'session:data', [['plan', 'pro'], ['mrr', '49']]])

Paso 3: Integración con API

// lib/crisp.ts — Enviar mensajes y gestionar conversaciones mediante API
const CRISP_ID = process.env.CRISP_IDENTIFIER!
const CRISP_KEY = process.env.CRISP_KEY!
const WEBSITE_ID = process.env.CRISP_WEBSITE_ID!

// Enviar un mensaje a una conversación
await fetch(`https://api.crisp.chat/v1/website/${WEBSITE_ID}/conversation/${sessionId}/message`, {
  method: 'POST',
  headers: {
    'Content-Type': 'application/json',
    Authorization: `Basic ${Buffer.from(`${CRISP_ID}:${CRISP_KEY}`).toString('base64')}`,
  },
  body: JSON.stringify({
    type: 'text',
    from: 'operator',
    origin: 'chat',
    content: '¡Gracias por contactarnos! Permíteme ayudarte.',
  }),
})

Pautas

  • Nivel gratuito: 2 operadores, conversaciones ilimitadas, widget de chat, aplicaciones móviles.
  • Pro ($25/mes): chatbot, base de conocimientos, llamadas de audio/vídeo, integraciones.
  • Usa datos de sesión para pasar contexto del usuario (plan, MRR, última acción) a los agentes de soporte.
  • El chatbot de Crisp puede gestionar preguntas frecuentes automáticamente antes de derivar a humanos.

Individual skills in this repo

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

TerminalSkills/skills

>- Run GitHub Actions locally with act. Use when a user asks to test GitHub Actions workflows locally, debug CI pipelines without pushing, or run workflows offline.

TerminalSkills/skills

>- You are an expert in AG2 (formerly AutoGen), the open-source multi-agent conversation framework. You help developers build systems where multiple AI agents collaborate through structured conversations — with tool use, human-in-the-loop, code execution, group chat orchestration, and nested conversations — for complex tasks like software development, research, and data analysis.

TerminalSkills/skills

>- Generate short-form videos with AI — script writing, text-to-speech narration, stock footage selection, subtitle generation, and video assembly. Use when: creating TikTok/YouTube Shorts/Reels content, automating video production, building content pipelines.

TerminalSkills/skills

>- Animate 3D objects and characters in Blender with Python. Use when the user wants to keyframe properties, create armatures and rigs, set up IK/FK chains, animate shape keys for facial animation, edit F-Curves, use the NLA editor to blend actions, add drivers for expression-based animation, or script any animation workflow in Blender.

TerminalSkills/skills

>- Automate motion capture and tracking workflows in Blender with Python. Use when the user wants to import BVH or FBX mocap data, retarget motion to armatures, track camera or object motion from video, solve camera motion, clean up motion capture data, or script any tracking pipeline in Blender.

TerminalSkills/skills

>- You are an expert in Bolt.new by StackBlitz, the AI-powered full-stack development environment that runs entirely in the browser. You help developers go from idea to deployed app in minutes using natural language prompts — Bolt generates complete applications with frontend, backend, database, and deployment, all running in a WebContainer without local setup.

TerminalSkills/skills

>- Assists with using Bun as an all-in-one JavaScript/TypeScript runtime, package manager, bundler, and test runner. Use when building HTTP servers, managing packages, running tests, or migrating from Node.js. Trigger words: bun, bun serve, bun install, bun test, bun build, javascript runtime, bun runtime.

TerminalSkills/skills

>- Self-host customer support with Chatwoot. Use when a user asks to set up open-source customer support, add live chat without SaaS costs, build a multi-channel inbox, or deploy a free Intercom alternative.

TerminalSkills/skills

>- You are an expert in Chi, the lightweight, idiomatic Go HTTP router built on `net/http`. You help developers build composable HTTP services using Chi's middleware stack, route groups, URL parameters, sub-routers, and context-based request scoping — providing Express-like ergonomics while staying 100% compatible with Go's standard library.

TerminalSkills/skills

When the user wants to edit, review, or improve existing marketing copy. Also use when the user mentions 'edit this copy,' 'review my copy,' 'copy feedback,' 'proofread,' 'polish this,' 'make this better,' or 'copy sweep.' This skill provides a systematic approach to editing marketing copy through multiple focused passes.

TerminalSkills/skills

>- Assists with building custom interactive data visualizations using D3.js. Use when creating charts, graphs, maps, force layouts, or hierarchical diagrams that require fine-grained control beyond what charting libraries provide. Trigger words: d3, data visualization, chart, svg, scales, force graph, treemap, choropleth.

TerminalSkills/skills

dbt (data build tool) transforms data in your warehouse using SQL SELECT statements. Learn project setup, models, tests, documentation, incremental materializations, and integration with data warehouses like PostgreSQL, BigQuery, and Snowflake.

TerminalSkills/skills

>- You are an expert in dlt, the open-source Python library for building data pipelines. You help developers load data from any API, file, or database into warehouses and lakes using simple Python decorators — with automatic schema inference, incremental loading, and built-in data contracts. dlt is the "requests library for data pipelines.

TerminalSkills/skills

Data Version Control for ML projects. Track large datasets and models alongside Git, build reproducible ML pipelines, and run experiments with metric comparison. Works with any storage backend including S3, GCS, Azure, and local filesystems.

TerminalSkills/skills

>- You are an expert in E2B, the cloud platform for running AI-generated code in secure sandboxes. You help developers give AI agents the ability to execute code, install packages, read/write files, and run long processes in isolated cloud environments — each sandbox is a lightweight VM that boots in ~150ms with full Linux, filesystem, and networking.

TerminalSkills/skills

>- Transcode, convert, edit, and process audio and video with FFmpeg. Use when a user asks to convert video formats (webm to mp4, mkv to mp4), extract audio from video, compress video files, trim or cut clips, concatenate videos, add subtitles, create thumbnails, apply filters, change resolution or bitrate, re-encode media, create GIFs from video, add watermarks, normalize audio, stream media, or build automated media processing pipelines.

TerminalSkills/skills

>- Create advanced animations with GSAP. Use when building complex timelines, scroll-driven animations, SVG morphing, text animations, or high-performance web animations beyond CSS capabilities.

TerminalSkills/skills

>- Generate deterministic MP4 videos from HTML, CSS, media, and seekable animations using HeyGen's HyperFrames framework. Use when someone asks to "render HTML to video", "make a video with HyperFrames", "create a programmatic video", "turn an animation into MP4", "build a launch/product video from HTML", "render GSAP/Lottie/Three.js to video", or set up an agent-driven video pipeline. Covers init/preview/render/add/lint/inspect commands, data-* timing attributes, animation adapters, and the component catalog.

TerminalSkills/skills

When the user wants to perform load testing, stress testing, or performance testing of APIs and websites using k6. Also use when the user mentions "k6," "load test," "performance test," "stress test," "spike test," "soak test," "thresholds," "virtual users," or "VUs." For browser-based testing, see selenium.

TerminalSkills/skills

>- Lovable (formerly GPT Engineer) is a browser-based AI app builder that turns a natural-language description into a working full-stack web app with a built-in backend, authentication, database and one-click publishing. Use when the user wants to prototype or ship a web app with Lovable, write effective Lovable prompts, connect Supabase or GitHub, review generated security rules, or move a Lovable project into their own editor.

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