@robinpath/agent

@robinpath/agent

AI agent integration for Claude Code and OpenAI Codex — prompts, parsing, caching, retries, batch processing, classification, extraction, guards, and context management

Why use this module?

The agent module lets you:

• Configure pipeline settings for AI agent execution
• Send a prompt to Claude Code CLI and parse the structured response
• Send a prompt to OpenAI Codex CLI and parse the structured response
• Set global debug verbosity level (0=off, 1=info, 2=verbose, 3=trace)
• Set the log file path for debug output

All functions are callable directly from RobinPath scripts with a simple, consistent API.

Installation

robinpath add @robinpath/agent

Quick Start

No credentials needed — start using it right away:

agent.claude "analyze" {"question": "What is 2+2?", "expectedOutput": "NUMBER"} into $answer

Available Functions

Function	Description
agent.pipeline	Configure pipeline settings for AI agent execution
agent.claude	Send a prompt to Claude Code CLI and parse the structured response
agent.codex	Send a prompt to OpenAI Codex CLI and parse the structured response
agent.debug	Set global debug verbosity level (0=off, 1=info, 2=verbose, 3=trace)
agent.log	Set the log file path for debug output
agent.cost	Get pipeline cost and timing report for all executed steps
agent.notify	Configure notification settings for pipeline events
agent.model	Set or get the default AI model for all subsequent steps
agent.prompt	Load a prompt template from a file with {{variable}} substitution
agent.context	Manage conversation contexts for multi-turn AI interactions
agent.batch	Process an array of items through an AI prompt with concurrency control
agent.classify	Classify text into one of the given categories (sugar for common AI task)
agent.extract	Extract structured fields from unstructured text as a JSON object
agent.guard	Validate AI output against rules before passing it forward in the pipeline

Examples

Send a prompt to Claude Code CLI and parse the structured response

agent.claude "analyze" {"question": "What is 2+2?", "expectedOutput": "NUMBER"} into $answer

Send a prompt to OpenAI Codex CLI and parse the structured response

agent.codex "generate" {"question": "Write a hello world in Python", "expectedOutput": "CODE"} into $code

Set global debug verbosity level (0=off, 1=info, 2=verbose, 3=trace)

agent.debug 1

Integration with RobinPath

import { RobinPath } from "@wiredwp/robinpath";
import Module from "@robinpath/agent";

const rp = new RobinPath();
rp.registerModule(Module.name, Module.functions);
rp.registerModuleMeta(Module.name, Module.functionMetadata);

const result = await rp.executeScript(`
  agent.claude "analyze" {"question": "What is 2+2?", "expectedOutput": "NUMBER"} into $answer
`);

Full API Reference

See MODULE.md for complete documentation including all parameters, return types, error handling, and advanced examples.

Related Modules

• @robinpath/openai — OpenAI module for complementary functionality
• @robinpath/anthropic — Anthropic module for complementary functionality
• @robinpath/ai — AI module for complementary functionality
• @robinpath/deepl — DeepL module for complementary functionality
• @robinpath/translate — Translate module for complementary functionality

License

MIT