elevenlabs-agents▌
jezweb/claude-skills · updated Apr 8, 2026
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Build production-ready conversational AI voice agents with ElevenLabs Platform.
- ›Supports React, React Native, Swift, and JavaScript SDKs with dashboard or CLI-based agent configuration
- ›Add client-side and webhook-based server tools, upload knowledge bases for RAG, and configure voice, LLM, system prompt, and first message
- ›Includes signed URL authentication pattern, agent versioning for A/B testing, and dynamic variable injection for user context
- ›CLI provides init, deploy, test, an
ElevenLabs Agent Builder
Build a production-ready conversational AI voice agent. Produces a configured agent with tools, knowledge base, and SDK integration.
Packages
npm install @elevenlabs/react # React SDK
npm install @elevenlabs/client # JavaScript SDK (browser + server)
npm install @elevenlabs/react-native # React Native SDK
npm install @elevenlabs/elevenlabs-js # Full API (server only)
npm install -g @elevenlabs/agents-cli # CLI ("Agents as Code")
DEPRECATED: @11labs/react, @11labs/client -- uninstall if present.
Server-only warning: @elevenlabs/elevenlabs-js uses Node.js child_process and won't work in browsers. Use @elevenlabs/client for browser environments, or create a proxy server.
Workflow
Step 1: Create Agent via Dashboard or CLI
Dashboard: https://elevenlabs.io/app/conversational-ai -> Create Agent
CLI (Agents as Code):
elevenlabs agents init
elevenlabs agents add "Support Bot" --template customer-service
# Edit agent_configs/support-bot.json
elevenlabs agents push --env dev
Templates: default, minimal, voice-only, text-only, customer-service, assistant.
Configure:
- Voice -- Choose from 5000+ voices or clone
- LLM -- GPT, Claude, Gemini, or custom
- System prompt -- Use the 6-component framework below
- First message -- What the agent says when conversation starts
Step 2: Write the System Prompt
Use the 6-component framework for effective agent prompts:
1. Personality -- who the agent is:
You are [NAME], a [ROLE] at [COMPANY].
You have [EXPERIENCE]. Your traits: [LIST TRAITS].
2. Environment -- communication context:
You're communicating via [phone/chat/video].
Consider [environmental factors]. Adapt to [context].
3. Tone -- speech patterns and formality:
Tone: Professional yet warm. Use contractions for natural speech.
Avoid jargon. Keep responses to 2-3 sentences. Ask one question at a time.
4. Goal -- objectives and success criteria:
Primary Goal: Resolve customer issues on the first call.
Success: Customer verbally confirms issue is resolved.
5. Guardrails -- boundaries and ethics:
Never: provide medical/legal/financial advice, share confidential info.
Always: verify identity before account access, document interactions.
Escalation: customer requests manager, issue beyond knowledge base.
6. Tools -- available functions and when to use them:
1. lookup_order(order_id) -- Use when customer mentions an order.
2. transfer_to_supervisor() -- Use when issue requires manager approval.
Always explain what you're doing before calling a tool.
Step 3: Add Tools
Client-side tools (run in browser):
const clientTools = {
updateCart: {
description: "Add or remove items from the shopping cart",
parameters: z.object({
action: z.enum(['add', 'remove']),
item: z.string(),
quantity: z.number().min(1)
}),
handler: async ({ action, item, quantity }) => {
const cart = getCart();
action === 'add' ? cart.add(item, quantity) : cart.remove(item, quantity);
return { success: true, total: cart.total, items: cart.items.length };
}
},
navigate: {
description: "Navigate user to a different page",
parameters: z.object({ url: z.string().url() }),
handler: async ({ url }) => { window.location.href = url; return { success: true }; }
}
};
Server-side tools (webhooks):
{
"name": "get_weather",
"description": "Fetch current weather for a city",
"url": "https://api.weather.com/v1/current",
"method": "GET",
"parameters": {
"type": "object",
"properties": {
"city": { "type": "string", "description": "City name" }
},
"required": ["city"]
},
"headers": {
"Authorization": "Bearer {{secret__weather_api_key}}"
}
}
Use {{secret__key_name}} for API keys in webhook headers -- never hardcode.
MCP Tools -- CRITICAL COMPATIBILITY NOTE:
ElevenLabs labels their MCP integration as "Streamable HTTP" but does NOT support the actual MCP 2025-03-26 Streamable HTTP spec (SSE responses). ElevenLabs expects:
- Plain JSON responses (
application/json), NOT SSE (text/event-stream) - Protocol version
2024-11-05, NOT2025-03-26 - Simple JSON-RPC over HTTP with direct JSON responses
What does NOT work:
- Official MCP SDK's
createMcpHandler(returns SSE) - Cloudflare Agents SDK
McpServer.serve()(returns SSE) - Any server returning
Content-Type: text/event-stream
Working MCP server pattern for ElevenLabs:
import { Hono } from 'hono';
import { cors } from 'hono/cors';
const tools = [{
name: "my_tool",
description: "Tool description",
inputSchema: {
type: "object",
properties: { param1: { type: "string", description: "Description" } },
required: ["param1"]
}
}];
async function handleMCPRequest(request, env) {
const { id, method, params } = request;
switch (method) {
case 'initialize':
return {
jsonrpc: '2.0', id,
result: {
protocolVersion: '2024-11-05', // MUST be 2024-11-05
serverInfo: { name: 'my-mcp', version: '1.0.0' },
capabilities: { tools: {} }
}
};
case 'tools/list':
return { jsonrpc: '2.0', id, result: { tools } };
case 'tools/call':
const result = await handleTool(params.name, params.arguments, env);
return { jsonrpc: '2.0', id, result };
default:
return { jsonrpc: '2.0', id, error: { code: -32601, message: `Unknown: ${method}` } }how to use elevenlabs-agentsHow to use elevenlabs-agents on Cursor
AI-first code editor with Composer
1Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
- ›Cursor installed and configured on your development machine
- ›Node.js version 16.0+ with npm package manager (verify with
node --version) - ›Active project directory or workspace where you want to add elevenlabs-agents
2Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
$npx skills add https://github.com/jezweb/claude-skills --skill elevenlabs-agentsThe skills CLI fetches elevenlabs-agents from GitHub repository jezweb/claude-skills and configures it for Cursor.
3Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
◆ Which agents do you want to install to?││ ── Universal (.agents/skills) ── always included ────│ • Amp│ • Antigravity│ • Cline│ • Codex│ ●Cursor(selected)│ • Cursor│ • Windsurf4Verify installation
Confirm successful installation by checking the skill directory location:
.cursor/skills/elevenlabs-agentsReload or restart Cursor to activate elevenlabs-agents. Access the skill through slash commands (e.g., /elevenlabs-agents) or your agent's skill management interface.
⚠Security & Verification Notice
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.
Additional Resources
List & Monetize Your Skill
Submit your Claude Code skill and start earning
GET_STARTED →Use Cases▌
User Story & Requirements Generation
Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
✓Reduce spec writing time by 50%, ensure comprehensive coverage
Competitive Analysis
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
✓Complete competitive research in 2 hours instead of 2 days
Roadmap Prioritization
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
✓Make data-driven prioritization decisions faster
Stakeholder Communication
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
✓Save 3-5 hours/week on communication overhead
Implementation Guide▌
Prerequisites
- ›Claude Desktop or compatible AI client
- ›Access to product documentation and roadmap tools (Jira, Notion, etc.)
- ›Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
- ›Stakeholder contact information and communication channels
Time Estimate
30-60 minutes to see productivity improvements
Installation Steps
- 1.Install product management skill
- 2.Start with user story generation for known feature
- 3.Progress to competitive analysis: research 2-3 competitors
- 4.Use for roadmap prioritization: apply RICE/ICE scoring
- 5.Draft stakeholder communications and refine based on feedback
- 6.Build template library for recurring PM tasks
- 7.Share effective prompts with product team
Common Pitfalls
- ⚠Not validating competitive research—verify facts before sharing
- ⚠Accepting user stories without involving engineering team
- ⚠Over-relying on frameworks without qualitative judgment
- ⚠Not customizing outputs to company culture and communication style
- ⚠Skipping stakeholder validation of generated requirements
Best Practices▌
✓ Do
- +Validate research and competitive analysis with real data
- +Collaborate with engineering when generating technical requirements
- +Customize frameworks and templates to your company context
- +Use skill for first drafts, refine with stakeholder input
- +Document successful prompt patterns for PM tasks
- +Combine AI efficiency with human judgment and intuition
✗ Don't
- −Don't publish competitive analysis without fact-checking
- −Don't finalize user stories without engineering review
- −Don't make prioritization decisions solely on AI scoring
- −Don't skip customer validation of generated requirements
- −Don't ignore company-specific context and culture
💡 Pro Tips
- ★Provide context: company goals, constraints, customer feedback
- ★Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
- ★Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
- ★Use skill for 70% generation + 30% customization to company needs
When to Use This▌
✓ Use When
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid When
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
Learning Path▌
- 1Basic: user stories, feature specs, status updates
- 2Intermediate: competitive analysis, prioritization frameworks, PRDs
- 3Advanced: product strategy, go-to-market planning, OKR setting
- 4Expert: product vision, market positioning, business model innovation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
general reviewsRatings
4.8★★★★★68 reviews- ★★★★★Arya Okafor· Dec 28, 2024
I recommend elevenlabs-agents for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Pratham Ware· Dec 20, 2024
elevenlabs-agents is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Chinedu Abbas· Dec 12, 2024
elevenlabs-agents reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Dev Reddy· Dec 8, 2024
elevenlabs-agents is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Ama Mensah· Dec 8, 2024
We added elevenlabs-agents from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Arya Bansal· Dec 4, 2024
Keeps context tight: elevenlabs-agents is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Arjun Flores· Dec 4, 2024
Solid pick for teams standardizing on skills: elevenlabs-agents is focused, and the summary matches what you get after install.
- ★★★★★Tariq Dixit· Nov 27, 2024
Keeps context tight: elevenlabs-agents is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Luis Thomas· Nov 23, 2024
We added elevenlabs-agents from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Emma Farah· Nov 23, 2024
elevenlabs-agents has been reliable in day-to-day use. Documentation quality is above average for community skills.
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