Agent skill

Lindy Multi Env Setup

by jeremylongshore in jeremylongshore/tons-of-skills-marketplace

Configure Lindy AI across development, staging, and production environments.

MITAuto-check: notesDevOps & Cloud

Install Lindy Multi Env Setup

skills CLI
$ npx skills add jeremylongshore/tons-of-skills-marketplace --skill lindy-multi-env-setup -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install jeremylongshore/tons-of-skills-marketplace lindy-multi-env-setup --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/jeremylongshore/tons-of-skills-marketplace.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/.curated/lindy-multi-env-setup .claude/skills/lindy-multi-env-setup && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
lindy-multi-env-setup
GitHub stars
2.8k
Token cost
~1.9k tokens
SKILL.md length
347 words
Files
3 (incl. references)
Skills in repo
3,342
Repo updated
First seen
Licence
MIT

At a glance

Configure Lindy AI across development, staging, and production environments.

  • Works in 6 steps: Create Separate Workspaces → Environment Configuration → Startup Validation → …
  • Setting up isolated workspaces
  • SKILL.md covers Overview, Prerequisites, Environment Strategy and Instructions, plus 5 more sections
  • Calls gh, aws and gcloud; reaches public.lindy.ai; needs LINDY_API_KEY and LINDY_WEBHOOK_SECRET

What it does

Lindy Multi Env Setup is an agent skill from jeremylongshore/tons-of-skills-marketplace. Configure Lindy AI across development, staging, and production environments. Use when setting up isolated workspaces, per-environment secrets, or environment-specific agent configurations. Trigger with phrases like "lindy environments", "lindy staging", "lindy dev prod", "lindy environment setup", "lindy workspace isolation".

Its SKILL.md is about 1.9k tokens, which your agent loads only when the skill is triggered. The skill folder holds 3 other files, including reference files (for example `references/implementation-guide.md` and `references/implementation.md`). Compatibility notes: Designed for Claude Code

It sits in DevOps & Cloud, covering Git worktrees. The repository describes itself as: Model-agnostic agent-skills platform with a harness-free canonical layer, verified adapters, and the ccpi package manager. Explore at tonsofskills.com. The licence is MIT.

When your agent uses it

  • Setting up isolated workspaces
  • Per-environment secrets
  • Environment-specific agent configurations
  • With phrases like lindy environments

Example prompts

  • “lindy environments”
  • “lindy staging”
  • “lindy dev prod”
  • “/lindy-multi-env-setup”

Requirements

  • A credential in LINDY_API_KEY
  • A credential in LINDY_WEBHOOK_SECRET
  • Compatibility (from SKILL.md): Designed for Claude Code
  • Pre-approved tools (allowed-tools): Read, Write, Edit, Bash(aws:*), Bash(gcloud:*), Bash(vault:*)

Workflow steps

6 steps, taken from the step headings in SKILL.md.

  1. Create Separate Workspaces
  2. Environment Configuration
  3. Startup Validation
  4. Secret Management
  5. Agent Promotion (Dev to Staging to Prod)
  6. CI/CD Integration

What it can do on your machine

Read from SKILL.md and the folder at commit cfae287. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves these tools, so the agent can use them without asking each time:

    • Read
    • Write
    • Edit
    • Bash(aws:*)
    • Bash(gcloud:*)
    • Bash(vault:*)

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • gh
    • aws
    • gcloud

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Hosts in commands or code, which the agent is likely to contact:

    • public.lindy.ai

    Also links to:

    • docs.lindy.ai

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names these keys or tokens, usually read from environment variables:

    • LINDY_API_KEY
    • LINDY_WEBHOOK_SECRET

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

  • Compatibility

    Designed for Claude Code

    From compatibility in the SKILL.md frontmatter.

Context cost

Lindy Multi Env Setup loads about 1.9k tokens when it runs, and up to ~4.1k if it reads all its reference files. Until then it costs about 87 tokens; SKILL.md has 347 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~87
When it runs · the whole SKILL.md, loaded when a task matches
~1.9k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~4.1k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check: notes

The automated check noted patterns worth knowing about, such as sudo or a known installer.

  • NoteMentions a .env fileSKILL.md:44
    | Development | `dev-workspace` | `.env.local` | Debug prompts, test integrations |
  • NoteMentions a .env fileSKILL.md:136
    # Development — .env.local (gitignored)

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from jeremylongshore/tons-of-skills-marketplace at commit cfae287, republished under its MIT licence (© jeremylongshore). 347 words, ~1,871 tokens.

Download SKILL.mdSave it as .claude/skills/lindy-multi-env-setup/SKILL.md (or your agent's skills folder). This skill also uses 2 other files; get the full folder from GitHub.
name
lindy-multi-env-setup
description
Configure Lindy AI across development, staging, and production environments. Use when setting up isolated workspaces, per-environment secrets, or environment-specific agent configurations. Trigger with phrases like "lindy environments", "lindy staging", "lindy dev prod", "lindy environment setup", "lindy workspace isolation".
allowed-tools
Read, Write, Edit, Bash(aws:*), Bash(gcloud:*), Bash(vault:*)
compatibility
Designed for Claude Code
version
1.20.0
license
MIT
author
Jeremy Longshore <jeremy@intentsolutions.io>
tags
saas, lindy, deployment

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
typescript
// 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
typescript
// 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
bash
# 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
yaml
# .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

Output

Produce an environment register listing each workspace, public callback host, credential reference, integration owner, promotion source, last smoke-test result, and rollback target. Record only secret identifiers and redacted URL forms; never copy credential values, private webhook paths, customer data, or production connection exports between environments.

Examples

Promote a tested development template into staging, reconnect every integration with staging-only accounts, replace callback configuration, and record a synthetic smoke-test task ID. Before production promotion, prove the staging register contains no production secret reference. If that isolation check fails, stop promotion, rotate the exposed credential, and correct the environment map.

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.

© jeremylongshore, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 2 other files (references) in skills/.curated/lindy-multi-env-setup of jeremylongshore/tons-of-skills-marketplace.

  • SKILL.md
  • references/implementation-guide.md
  • references/implementation.md

Open the folder on GitHubat commit cfae287

Compare with similar skills

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Questions about Lindy Multi Env Setup

What does Lindy Multi Env Setup do?

Configure Lindy AI across development, staging, and production environments. Lindy Multi Env Setup is an agent skill from jeremylongshore/tons-of-skills-marketplace. Configure Lindy AI across development, staging, and production environments.

When should I use Lindy Multi Env Setup?

Lindy Multi Env Setup fits situations like: setting up isolated workspaces; per-environment secrets; environment-specific agent configurations; with phrases like lindy environments.

How do I install Lindy Multi Env Setup in Claude Code?

Run `npx skills add jeremylongshore/tons-of-skills-marketplace --skill lindy-multi-env-setup -a claude-code`. Or copy the skill folder (skills/.curated/lindy-multi-env-setup in jeremylongshore/tons-of-skills-marketplace) into .claude/skills/lindy-multi-env-setup in your project. Claude Code loads it when a task matches its description.

How do I install Lindy Multi Env Setup in Codex?

Run `npx skills add jeremylongshore/tons-of-skills-marketplace --skill lindy-multi-env-setup -a codex`. Or copy the skill folder (skills/.curated/lindy-multi-env-setup in jeremylongshore/tons-of-skills-marketplace) into .agents/skills/lindy-multi-env-setup in your project. Codex loads it when a task matches its description.

Can I use Lindy Multi Env Setup in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add jeremylongshore/tons-of-skills-marketplace --skill lindy-multi-env-setup -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/lindy-multi-env-setup, .gemini/skills/lindy-multi-env-setup, .github/skills/lindy-multi-env-setup and .opencode/skills/lindy-multi-env-setup in your project.

What does Lindy Multi Env Setup need to run?

Going by SKILL.md and its folder, Lindy Multi Env Setup needs the command-line tools its instructions call (gh, aws and gcloud) and credentials named LINDY_API_KEY and LINDY_WEBHOOK_SECRET. Our summary lists: A credential in LINDY_API_KEY; A credential in LINDY_WEBHOOK_SECRET. Its frontmatter pre-approves these tools: Read, Write, Edit, Bash(aws:*), Bash(gcloud:*), Bash(vault:*). Compatibility (from SKILL.md): Designed for Claude Code.

Does Lindy Multi Env Setup access the network?

SKILL.md names 2 domains. In commands or code: public.lindy.ai; the agent is likely to contact it when it follows the instructions. As links in the text: docs.lindy.ai. This is read from the text; nothing was executed.

Is Lindy Multi Env Setup safe to install?

Our automated static check of SKILL.md found notes only (mentions a .env file), nothing it rates as a warning. It is not a guarantee. Review the folder before installing.

What licence does Lindy Multi Env Setup use?

Lindy Multi Env Setup is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Lindy Multi Env Setup use?

About 1.9k tokens (SKILL.md is roughly 7.5k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 2.2k tokens, read only when the agent opens those files.

What are the alternatives to Lindy Multi Env Setup?

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Who maintains Lindy Multi Env Setup?

jeremylongshore (a GitHub user) maintains it in jeremylongshore/tons-of-skills-marketplace, which has 2,827 GitHub stars. The repository holds 3,342 skills in this directory. The repository was last updated on October 10, 2026.

Source: jeremylongshore/tons-of-skills-marketplace on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.