Metadata-Version: 2.4
Name: agentic-toolbelt
Version: 0.1.19
Summary: Packages agent payload assets and installs them into a project via the agentic-set CLI.
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Programming Language :: Python :: 3.13
Requires-Python: >=3.9
Description-Content-Type: text/markdown
Provides-Extra: test
Requires-Dist: pytest>=8; extra == "test"
Requires-Dist: tomli>=1.1.0; python_version < "3.11" and extra == "test"
Dynamic: requires-python

# Agentic Toolbelt

**Author:** Roberto Del Prete

`agentic-toolbelt` packages a reproducible baseline for agent-driven projects. It ships a curated set of agent instructions, Codex runtime templates, and supporting assets, then installs them into a target repository through a single CLI.

`pip install` gives you the package. `agentic-set` applies the payload to the current project directory.

Built for teams that want a consistent agent baseline across repositories without hand-assembling boilerplate.

## What It Installs

Running `agentic-set` copies the packaged baseline into the directory where you launch it:

- `.agents`
- `.codex`
- `.github`
- `.tasks`
- `templates`
- `AGENTS.md`

It also materializes the active Codex runtime:

- `.codex/config.toml`
- `.codex/agents/*.toml`

Each file in `.codex/agents/*.toml` is a standalone Codex custom agent definition with its own `name`, `description`, and `developer_instructions`.

The copied `templates/codex/` directory also includes package reference material such as `routing-profiles.toml`, which documents the shipped orchestration policy without extending the active Codex runtime config.

The bootstrap also creates a root `.tasks/` workspace. Use the packaged `task-breakdown` skill when a request is too large or ambiguous to plan in one pass; it narrows the problem into numbered JSON briefs such as `.tasks/001-auth-boundary.json`.

The result is a project that can resolve named agents such as `planner` and `implementer` immediately after bootstrap.

## Install

`agentic-toolbelt` supports Python 3.9 and newer.

From the repository root:

```bash
python -m pip install .
```

Then bootstrap the current project:

```bash
agentic-set
```

For local development and test runs:

```bash
python -m pip install -e ".[test]"
```

That registers the `agentic-set` console script in your environment. It does not copy files into a project until you run the command.

## Usage

From any project directory:

```bash
agentic-set
```

By default, existing destination paths are preserved. Use `--force` to overwrite `.agents`, `.codex`, `.github`, `.tasks`, `templates`, and `AGENTS.md` when you need to refresh a project.

```bash
agentic-set --force
```

The CLI uses temporary staging during copy operations so installs are predictable and partial writes are avoided.

## Why It Matters

This repository standardizes how autonomous agents are configured, launched, and governed across codebases. The goal is a consistent baseline that is easy to bootstrap, easy to inspect, and straightforward to extend.

## Docs

A visual overview is available at:

- `docs/index.html`

Open it in a browser to review the repo concept, architecture, and CLI workflows.

## Development

- The Python package entrypoint is declared in both `setup.py` and `pyproject.toml`.
- The current package version is maintained in both files as well.

## Release Checks

Build and verify the distributable artifacts from the repository root:

```bash
python -m pytest
python -m build
python -m twine check dist/*
```

For a smoke test of the built wheel, install it into a clean environment and run:

```bash
agentic-set --help
```
