agent-docs-creator

The agent analyzes AI source code to generate structured, clear, and complete documentation in a consistent template, supporting multiple languages.

  • BeeAI
beeai run agent-docs-creator
Try locally in GUI

Example requests

beeai run agent-docs-creator "function exampleAgent() { /* AI agent source code here */ }"

Description

The agent is designed to create structured documentation for AI agents by processing their source code. It aims to provide a comprehensive overview by extracting critical details and formatting them into a predefined documentation template. This ensures that the documentation is clear, complete, and consistent across different AI agents.

How It Works

The agent uses a chat model to analyze the input source code. It constructs a structured document consisting of a short description and a detailed markdown-formatted full description. The short description provides a high-level summary, while the full description includes sections like "How It Works," "Input Parameters," "Output Structure," "Key Features," "Use Cases," and "Example Usage." The agent's output is generated by simulating a conversation between system and user messages to refine the output to meet the documentation standards.

Input Parameters

The agent requires the following input parameter:

  • text (string) – String that represents the source code of the AI agent to be documented.

Output Structure

The agent returns an object with the following structure:

  • text (string) – The structured documentation generated in markdown format, including both the short and full description sections.

Key Features

  • Automated Documentation Generation – Transforms AI agent source code into structured documentation.
  • Consistent Template – Uses a predefined template to ensure uniformity across different documentations.
  • Multi-Language Support – Capable of processing AI agents written in various programming languages.
  • Interactive Clarification – Includes logic to request additional details if the source code lacks sufficient information.

Use Cases

  • AI Agent Cataloging – Streamlines the creation of documentation for AI agents to be included in catalogs or repositories.
  • Source Code Analysis – Provides insights into the functionality and features of AI agents by examining their source code.
  • Technical Documentation Enhancement – Enhances the quality and clarity of technical documentation for AI solutions.