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Basic Information

Meta Agent is a Python command-line tool that automatically generates production-ready AI agents from plain English descriptions. It is designed to let developers, solutions architects, rapid prototypers, and hobbyists create working agents without manually writing YAML specifications. From a short natural language prompt or interactive session the tool parses requirements, plans tasks, generates code, unit tests, guardrails, and any custom tools needed, then outputs a complete project structure including generated agent code, tests, and configuration. The project leverages the OpenAI SDK for LLM capabilities and requires an OpenAI API key. It also supports optional YAML and JSON spec files, project templates, and telemetry. The repo includes CLI commands for create, init, template management, and a dashboard for exported metrics.

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App Details

Features
Meta Agent emphasizes natural language input and an interactive CLI that guides users through agent creation. It generates full working agents instantly, including automatic guardrails, validation logic, and comprehensive unit tests. The tool can create custom tools when required and offers a template system for reusable patterns. Users can preview generated specifications, enable privacy-safe logging with a no-sensitive-logs flag, and view telemetry and metrics via a dashboard or export. Supported input formats include plain text, interactive prompts, YAML, and JSON. The architecture described includes a planning engine, sub-agent manager, tool designer, guardrail designer, and template system. Development tooling and requirements such as Python 3.11+, tests, linters, and typical project structure are provided.
Use Cases
Meta Agent reduces the time and expertise needed to build AI agents by automating specification parsing, task planning, tool generation, safety guardrails, and test creation. It removes the need to handcraft YAML specifications for most users, allowing product managers and non-experts to describe desired behavior in plain English while producing code that developers can further customize. The generated projects include tests and monitoring hooks to support production readiness and observability. Example use cases in the repository include data processing agents and web scraping agents with constraints such as rate limiting and robots.txt compliance. The CLI and templates accelerate prototyping, and the telemetry and privacy options help with integration and secure deployment workflows.

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