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Overview

The Nudgen CLI is designed with an AI-First approach. While it provides a beautiful TUI for humans, every command is also optimized for machine-to-machine communication.

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The Agentic Pattern

When an AI agent (like a Claude, GPT, or specialized automation agent) uses the CLI, it should follow these patterns:
  1. JSON Output: Append --json to every command to get machine-parseable data.
  2. Context Awareness: Always verify the team context before performing operations.
  3. Non-Interactive: Use flags to bypass interactive TUI prompts.

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JSON Automation

Every list and status command supports a --json flag. This returns a clean JSON structure instead of a formatted table. 
# Get all campaigns as JSON
nudgen campaigns list --json

# Get contacts in current team
nudgen contacts list --json

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Multi-tenant Workflow for Agents

Since Nudgen supports multiple teams, an agent must ensure it is operating on the correct team before creating or updating resources. Recommended Workflow:
  1. Check Current Team: 
    nudgen teams current --json
  2. Switch Team (if needed): If the id from the previous step doesn’t match the target team, switch: 
    nudgen teams switch <target-team-id>
  3. Execute Data Command: Proceed with campaigns, contacts, or brand commands.

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Best Practices for Agent Developers

  • Error Handling: Monitor the exit code of CLI commands. A non-zero exit code indicates an error (validation, network, or auth).
  • Rate Limiting: The CLI communicates with the Nudgen API. Ensure your agent scripts handle potential rate limits gracefully.
  • Silent Mode: If a command doesn’t support a specific flag for every prompt, ensure your agent can handle stdout/stderr streams without getting stuck in a TUI loop.