LI

lindy-multi-env-setup

Isolate Lindy AI environments using dedicated workspaces and environment-specific configuration.

Install

mkdir -p .claude/skills/lindy-multi-env-setup && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/8987" && unzip -o skill.zip -d .claude/skills/lindy-multi-env-setup && rm skill.zip

Installs to .claude/skills/lindy-multi-env-setup

Activation

This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.

Configure Lindy AI across development, staging, and production environments.
76 charsno explicit “when” trigger
Advanced

Key capabilities

  • Isolate agents across development, staging, and production
  • Manage environment-specific API keys and secrets
  • Implement environment-aware deployment logic
  • Validate environment configurations at startup

How it works

Agents are deployed into separate workspaces for each environment, using environment-specific API keys and secret management to ensure isolation.

Inputs & outputs

You give it
Environment-specific configuration and secrets
You get back
Isolated agent execution in dedicated workspaces

When to use lindy-multi-env-setup

  • Set up isolated workspace environments
  • Manage environment-specific secrets
  • Implement multi-environment deployment logic
  • Prevent cross-environment data leakage

About this skill

Lindy Multi-Environment Setup

Overview

Isolate Lindy AI agents across development, staging, and production using separate workspaces, dedicated API keys, and environment-specific webhook configurations. Lindy agents live in workspaces — each environment should use its own workspace to prevent cross-environment data leakage.

Prerequisites

  • Multiple Lindy workspaces (one per environment) or Enterprise plan
  • Secret management solution (env vars, Vault, AWS/GCP secrets)
  • CI/CD pipeline with environment-aware deployment
  • Application with environment detection logic

Environment Strategy

EnvironmentWorkspaceAPI Key SourceAgent Config
Developmentdev-workspace.env.localDebug prompts, test integrations
Stagingstaging-workspaceCI/CD secretsProduction-like, test data
Productionprod-workspaceSecret managerHardened prompts, live integrations

Instructions

Step 1: Create Separate Workspaces

  1. Log in at
  2. Create workspace for each environment: [company]-dev, [company]-staging, [company]-prod
  3. Generate separate API keys in each workspace
  4. Store each key in the appropriate secret store

Step 2: Environment Configuration

// config/lindy.ts — Environment-aware Lindy configuration
interface LindyConfig {
  apiKey: string;
  webhookUrl: string;
  webhookSecret: string;
  workspace: string;
  model: string;
}

function getLindyConfig(): LindyConfig {
  const env = process.env.NODE_ENV || 'development';

  const configs: Record<string, LindyConfig> = {
    development: {
      apiKey: process.env.LINDY_API_KEY_DEV!,
      webhookUrl: process.env.LINDY_WEBHOOK_URL_DEV!,
      webhookSecret: process.env.LINDY_WEBHOOK_SECRET_DEV!,
      workspace: 'dev',
      model: 'gemini-flash', // Cheap model for dev
    },
    staging: {
      apiKey: process.env.LINDY_API_KEY_STAGING!,
      webhookUrl: process.env.LINDY_WEBHOOK_URL_STAGING!,
      webhookSecret: process.env.LINDY_WEBHOOK_SECRET_STAGING!,
      workspace: 'staging',
      model: 'claude-sonnet', // Match prod model
    },
    production: {
      apiKey: process.env.LINDY_API_KEY_PROD!,
      webhookUrl: process.env.LINDY_WEBHOOK_URL_PROD!,
      webhookSecret: process.env.LINDY_WEBHOOK_SECRET_PROD!,
      workspace: 'production',
      model: 'claude-sonnet',
    },
  };

  const config = configs[env];
  if (!config) throw new Error(`Unknown environment: ${env}`);
  return config;
}

export const lindyConfig = getLindyConfig();

Step 3: Startup Validation

// validate-env.ts — Fail fast if Lindy config is missing
import { z } from 'zod';

const LindyEnvSchema = z.object({
  LINDY_API_KEY: z.string().min(1, 'LINDY_API_KEY required'),
  LINDY_WEBHOOK_SECRET: z.string().min(1, 'LINDY_WEBHOOK_SECRET required'),
  LINDY_WEBHOOK_URL: z.string().url('LINDY_WEBHOOK_URL must be valid URL'),
});

export function validateLindyEnv() {
  const result = LindyEnvSchema.safeParse({
    LINDY_API_KEY: process.env.LINDY_API_KEY,
    LINDY_WEBHOOK_SECRET: process.env.LINDY_WEBHOOK_SECRET,
    LINDY_WEBHOOK_URL: process.env.LINDY_WEBHOOK_URL,
  });

  if (!result.success) {
    console.error('Lindy environment validation failed:');
    result.error.issues.forEach(i => console.error(`  - ${i.path}: ${i.message}`));
    process.exit(1);
  }

  console.log('Lindy environment validated successfully');
}

Step 4: Secret Management

# Development — .env.local (gitignored)
LINDY_API_KEY=lnd_dev_xxxxxxxxxxxx
LINDY_WEBHOOK_URL=https://public.lindy.ai/api/v1/webhooks/dev-id
LINDY_WEBHOOK_SECRET=whsec_dev_xxxxxxxxxxxx

# Staging — CI/CD secrets (GitHub Actions)
gh secret set LINDY_API_KEY_STAGING --body "lnd_staging_xxxx"
gh secret set LINDY_WEBHOOK_SECRET_STAGING --body "whsec_staging_xxxx"

# Production — Cloud secret manager
# AWS
aws secretsmanager create-secret \
  --name prod/lindy/api-key \
  --secret-string "lnd_prod_xxxxxxxxxxxx"

# GCP
echo -n "lnd_prod_xxxxxxxxxxxx" | \
  gcloud secrets create lindy-api-key-prod --data-file=-

Step 5: Agent Promotion (Dev to Staging to Prod)

1. Build and test agent in dev workspace
2. Share agent as Template
3. Import template into staging workspace
4. Re-authorize integrations with staging accounts
5. Update webhook URLs to staging endpoints
6. Test with staging data for 24-48 hours
7. Repeat for production workspace
8. Update webhook URLs to production endpoints
9. Verify all integrations authorized with production accounts

Critical: OAuth tokens, webhook URLs, and phone numbers do NOT transfer between workspaces. Each must be reconfigured per environment.

Step 6: CI/CD Integration

# .github/workflows/deploy.yml
jobs:
  deploy-staging:
    if: github.ref == 'refs/heads/develop'
    environment: staging
    env:
      LINDY_API_KEY: ${{ secrets.LINDY_API_KEY_STAGING }}
      LINDY_WEBHOOK_SECRET: ${{ secrets.LINDY_WEBHOOK_SECRET_STAGING }}
    steps:
      - run: npm run deploy:staging
      - run: npm run test:lindy:smoke

  deploy-prod:
    if: github.ref == 'refs/heads/main'
    environment: production
    env:
      LINDY_API_KEY: ${{ secrets.LINDY_API_KEY_PROD }}
      LINDY_WEBHOOK_SECRET: ${{ secrets.LINDY_WEBHOOK_SECRET_PROD }}
    steps:
      - run: npm run deploy:prod
      - run: npm run test:lindy:smoke

Error Handling

IssueCauseSolution
Dev agent hits prod dataShared workspaceUse separate workspaces per environment
Staging integration failsOAuth token expiredRe-authorize with staging service accounts
Webhook URL mismatchDev URL in prod configValidate webhook URLs at startup
Secret not found in CIMissing environment secretAdd via gh secret set per environment

Resources

Next Steps

Proceed to lindy-observability for monitoring and alerting.

When not to use it

  • Do not share workspaces across environments to prevent data leakage

Prerequisites

Multiple Lindy workspacesSecret management solutionCI/CD pipeline

Limitations

  • OAuth tokens, webhook URLs, and phone numbers do not transfer between workspaces

How it compares

This approach enforces strict workspace isolation rather than relying on a single shared environment for all development stages.

Compared to similar skills

lindy-multi-env-setup side by side with the closest alternatives in the catalog.

SkillInstallsUpdatedSafetyDifficulty
lindy-multi-env-setup (this skill)027dReviewAdvanced
ollama-setup1127dReviewBeginner
cloudrun-development12moNo flagsAdvanced
ideogram-deploy-integration127dCautionIntermediate

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