lindy-multi-env-setup
Configure Lindy AI across development, staging, and production environments. Use when setting up multi-environment deployments, configuring per-environment secrets, or implementing environment-specific Lindy configurations. Trigger with phrases like "lindy environments", "lindy staging", "lindy dev prod", "lindy environment setup", "lindy config by env".
- License 许可
- MIT
- 最近更新
- 2026-11-11
- Stars
- ★ 2.0k
- Forks
- 231
01 前言 Front Matter
- name
- lindy-multi-env-setup
- author
- Jeremy Longshore <jeremy@intentsolutions.io>
- license
- MIT
- version
- 1.0.0
- description
- Configure Lindy AI across development, staging, and production environments. Use when setting up multi-environment deployments, configuring per-environment secrets, or implementing environment-specific Lindy configurations. Trigger with phrases like "lindy environments", "lindy staging", "lindy dev prod", "lindy environment setup", "lindy config by env".
- allowed-tools
- Read, Write, Edit, Bash(aws:*), Bash(gcloud:*), Bash(vault:*)
03 SKILL.md 正文
Lindy Multi Env Setup
Overview
Configure Lindy AI across development, staging, and production environments.
Prerequisites
- Separate Lindy API keys per environment
- Secret management solution (Vault, AWS Secrets Manager, etc.)
- CI/CD pipeline with environment variables
- Environment detection in application
Instructions
Step 1: Create Environment Configuration
// config/lindy.ts
interface LindyConfig {
apiKey: string;
environment: 'development' | 'staging' | 'production';
baseUrl?: string;
timeout: number;
retries: number;
}
const configs: Record<string, LindyConfig> = {
development: {
apiKey: process.env.LINDY_DEV_API_KEY!,
environment: 'development',
timeout: 60000,
retries: 1,
},
staging: {
apiKey: process.env.LINDY_STAGING_API_KEY!,
environment: 'staging',
timeout: 45000,
retries: 2,
},
production: {
apiKey: process.env.LINDY_PROD_API_KEY!,
environment: 'production',
timeout: 30000,
retries: 3,
},
};
export function getLindyConfig(): LindyConfig {
const env = process.env.NODE_ENV || 'development';
return configs[env] || configs.development;
}
Step 2: Implement Environment Detection
// lib/lindy-client.ts
import { Lindy } from '@lindy-ai/sdk';
import { getLindyConfig } from '../config/lindy';
let client: Lindy | null = null;
export function getLindyClient(): Lindy {
if (!client) {
const config = getLindyConfig();
// Validate environment
if (config.environment === 'production') {
if (!config.apiKey.startsWith('lnd_prod_')) {
throw new Error('Production requires production API key');
}
}
client = new Lindy({
apiKey: config.apiKey,
timeout: config.timeout,
retries: config.retries,
});
}
return client;
}
Step 3: Configure Secrets by Environment
# AWS Secrets Manager structure
secrets/
├── lindy/development
│ └── api_key: lnd_dev_xxx
├── lindy/staging
│ └── api_key: lnd_stg_xxx
└── lindy/production
└── api_key: lnd_prod_xxx
// secrets/lindy.ts
import { SecretsManager } from '@aws-sdk/client-secrets-manager';
export async function getLindyApiKey(env: string): Promise<string> {
const client = new SecretsManager({ region: 'us-east-1' });
const response = await client.getSecretValue({
SecretId: `lindy/${env}`,
});
const secret = JSON.parse(response.SecretString!);
return secret.api_key;
}
Step 4: Environment-Specific Agents
// agents/config.ts
interface AgentMapping {
development: string;
staging: string;
production: string;
}
const agentMappings: Record<string, AgentMapping> = {
support: {
development: 'agt_dev_support',
staging: 'agt_stg_support',
production: 'agt_prod_support',
},
sales: {
development: 'agt_dev_sales',
staging: 'agt_stg_sales',
production: 'agt_prod_sales',
},
};
export function getAgentId(agentName: string): string {
const env = process.env.NODE_ENV || 'development';
const mapping = agentMappings[agentName];
if (!mapping) {
throw new Error(`Unknown agent: ${agentName}`);
}
return mapping[env as keyof AgentMapping];
}
Step 5: Add Environment Guards
// guards/production.ts
export function requireProduction(): void {
if (process.env.NODE_ENV !== 'production') {
throw new Error('This operation requires production environment');
}
}
export function preventProduction(): void {
if (process.env.NODE_ENV === 'production') {
throw new Error('This operation is not allowed in production');
}
}
// Usage
async function dangerousOperation() {
preventProduction();
// ... destructive test operation
}
async function productionOnlyOperation() {
requireProduction();
// ... production-only logic
}
Output
- Multi-environment configuration
- Environment detection logic
- Secure secret management
- Environment-specific agents
- Production safeguards
Error Handling
| Issue | Cause | Solution |
|---|---|---|
| Wrong key for env | Config error | Validate key prefix |
| Secret not found | Not provisioned | Create in secrets manager |
| Agent not found | Wrong environment | Check agent mapping |
Examples
Complete Environment Setup
// index.ts
import { getLindyClient } from './lib/lindy-client';
import { getAgentId } from './agents/config';
async function main() {
const lindy = getLindyClient();
const agentId = getAgentId('support');
console.log(`Environment: ${process.env.NODE_ENV}`);
console.log(`Agent: ${agentId}`);
const result = await lindy.agents.run(agentId, {
input: 'Test message',
});
console.log('Response:', result.output);
}
main().catch(console.error);
Resources
Next Steps
Proceed to lindy-observability for monitoring setup.
04 同仓库更多 Skills
web-artifacts-builder
Suite of tools for creating elaborate, multi-component claude.ai HTML artifacts using modern frontend web technologies (React, Tailwind CSS, shadcn/ui). Use for complex artifacts requiring state management, routing, or shadcn/ui components - not for simple single-file HTML/JSX artifacts.
webapp-testing
Toolkit for interacting with and testing local web applications using Playwright. Supports verifying frontend functionality, debugging UI behavior, capturing browser screenshots, and viewing browser logs.
neuropixels-analysis
Neuropixels neural recording analysis. Load SpikeGLX/OpenEphys data, preprocess, motion correction, Kilosort4 spike sorting, quality metrics, Allen/IBL curation, AI-assisted visual analysis, for Neuropixels 1.0/2.0 extracellular electrophysiology. Use when working with neural recordings, spike sorting, extracellular electrophysiology, or when the user mentions Neuropixels, SpikeGLX, Open Ephys, Kilosort, quality metrics, or unit curation.
skill-creator
Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Claude's capabilities with specialized knowledge, workflows, or tool integrations.
notebooklm
Use this skill to query your Google NotebookLM notebooks directly from Claude Code for source-grounded, citation-backed answers from Gemini. Browser automation, library management, persistent auth. Drastically reduced hallucinations through document-only responses.
slack-gif-creator
Knowledge and utilities for creating animated GIFs optimized for Slack. Provides constraints, validation tools, and animation concepts. Use when users request animated GIFs for Slack like "make me a GIF of X doing Y for Slack."