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Agenthatch

Agenthatch is a Python CLI framework that converts SKILL.md files into standalone, runnable AI agent packages through parsing, LLM inference and code generation.

Explore the practical guide ↓

Independent OpenViST project profile, based on linked sources.

Agenthatch — OpenViST project profile in Agent Frameworks.
OpenViST project illustration. See the linked sources for product details.
Understand the project

Practical overview

When it fits

Use Agenthatch when a skill already expressed as a SKILL.md needs to be packaged and run as a separate agent rather than used only as prompt instructions.

Who it is for

  • Developers who maintain reusable SKILL.md instruction files and want to package them as separate Python agents.
  • Teams seeking separate agent runtimes, tools and configurations for different skills.

Documented uses

  • Convert a SKILL.md into a standalone agent package.
  • Add a skill file to an agenthatch project and generate a runnable agent.
  • Use typed tool definitions and MCP integration in the generated package, as described by the repository.
Before you choose

Requirements & limits

The repository is public and identifies the project as MIT-licensed. Its README documents installation through pip.

  • The workflow requires an LLM provider during initialization and uses LLM inference in its pipeline.
  • The repository describes deterministic parsing as a separate first phase; later inference and code generation are part of the process.
  • Generated packages are described as including a pyproject.toml, CLI entry point, typed tool definitions, MCP integration and runtime configuration.
  • Python and command-line usage are central to the documented workflow.

Check current requirements in the official documentation. Source-based guidance does not mean OpenViST has run or independently tested this project.

Source-based practical guide

Set up and run an agent from a SKILL.md

Use the documented CLI sequence to add a local skill and run its named agent.

Before you start

  • Python package installation via pip
  • An LLM provider to initialize
  • A local SKILL.md file

Steps

  1. Install with the command below.

    Documented command
    pip install agenthatch

  2. Run agenthatch init to initialize with an LLM provider.

  3. Add the file with agenthatch skill add ./my-skill/SKILL.md.

  4. Create the agent with agenthatch hatch my-skill.

  5. Run it with agenthatch run my-skill.

Expected outcome

A standalone runnable agent generated from the named SKILL.md, according to the repository quick start.

Guide limitations

  • The README does not specify provider configuration details or define compatibility limits for SKILL.md inputs.
  • The listed commands are repository instructions, not evidence of an independently tested run.
Documentation 1 ↗
COMPARE OPTIONS

Compare options for AI coding assistance

These projects document a common task and share a project role. This is a source-based comparison, not an execution benchmark or a guarantee of interchangeability.

ProjectDocumented purposePlatformAccess and requirements
AgenthatchConvert a SKILL.md into a standalone agent package.CLIThe repository is public and identifies the project as MIT-licensed. Its README documents installation through pip.
DextoDefine agents in YAML with a model, tools, storage and permissions.CLI
Evidence and transparency

Sources & review

Official repository ↗
Source record details
Source availability
Active
Sources checked
7 October 2026
Original website title
agenthatch/agenthatch · Official homepage title · retained in its source language
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