good-start 0.1.1
Test whether a codebase's getting-started documentation is accurate and easy to follow
Requires Python: >=3.12
Keywords: agent, documentation, testing

# Good Start

Test whether a project's getting-started documentation is accurate and easy to follow, using an AI agent.

Good Start reads your project's setup instructions, attempts to follow them step by step, and reports back with a pass/fail result and actionable feedback.

## Installation

Requires Python 3.12+.

```sh
pip install good-start
```

Or with uv:

```sh
uv add good-start
```

## Prerequisites

Good Start uses the Anthropic API under the hood. Set your API key before running:

```sh
export ANTHROPIC_API_KEY=your-key-here
```

## CLI Usage

Check a project's documentation by running `good-start check` from the project root:

```sh
# Let the agent find the getting-started docs automatically
good-start check .

# Point it at a specific file
good-start check README.md
good-start check docs/GETTING_STARTED.md
```

The output is a color-coded pass/fail panel with the agent's findings. The exit code is 0 on success and 1 on failure, so it works in CI scripts.

Save the output to a file:

```sh
good-start check . > report.txt
```

## Pytest Plugin

Good Start ships as a pytest plugin that is automatically available once installed. No configuration or conftest imports needed.

### Basic usage

```python
def test_getting_started(good_start):
    result = good_start()
    assert result.passed, result.details
```

The `good_start` fixture is a callable that runs the agent and returns a `Result` object with:
- `result.passed` -- boolean indicating whether the agent completed the instructions successfully
- `result.details` -- summary of findings, with constructive feedback on failure

### Checking a specific file

```python
def test_quickstart(good_start):
    result = good_start("docs/QUICKSTART.md")
    assert result.passed, result.details
```

### Configuration

Configuration resolves in this order (highest priority first):

1. Direct call arguments: `good_start("SETUP.md")`
2. Marker keyword arguments: `@pytest.mark.good_start(target="SETUP.md")`
3. CLI options: `pytest --good-start-target=SETUP.md`
4. ini options in `pyproject.toml`
5. Default: `"."`

#### Marker-based configuration

```python
import pytest

@pytest.mark.good_start(target="INSTALL.md")
def test_install_docs(good_start):
    result = good_start()
    assert result.passed, result.details
```

#### Project-wide defaults in pyproject.toml

```toml
[tool.pytest.ini_options]
good_start_target = "docs/GETTING_STARTED.md"
good_start_prompt = "tests/prompts/custom.md"
```

#### Custom prompt templates

Supply your own prompt file to tailor the agent's behavior:

```python
def test_with_custom_prompt(good_start):
    result = good_start(prompt_path="tests/prompts/strict.md")
    assert result.passed, result.details
```

### Skipping agent tests

Tests using the `good_start` fixture are automatically marked with `@pytest.mark.good_start`. Skip them during fast iteration:

```sh
pytest -m "not good_start"
```

Or run only the documentation tests:

```sh
pytest -m good_start -v
```

### Failure output

When a test fails, the agent's detailed findings are appended to the pytest failure report, so you get actionable feedback directly in your CI output.