Documentation is essential for software maintainability, yet it’s often outdated, incomplete, or missing altogether. Developers spend countless hours writing and updating docs—time that could be spent building features. In 2025, AI-powered documentation generation is changing the game, and Sweet! CLI brings this capability directly to your terminal.

With Sweet! CLI, you can automatically generate API docs, READMEs, inline comments, and architecture diagrams—all tailored to your codebase. This guide shows you how to leverage AI for documentation, with practical examples and integration strategies.

The Documentation Debt Problem

Manual documentation creates several challenges:

  • Drifts from code: Docs become outdated as the code evolves
  • Inconsistent quality: Different authors have different styles and depth
  • Time‑consuming: Writing comprehensive docs can take longer than writing the code itself
  • Missing context: External tools often lack project‑specific knowledge

AI‑assisted documentation tools promise to solve these issues, but many are limited to generic templates or require separate platforms. Sweet! CLI operates inside your development environment, understanding your codebase’s structure, dependencies, and patterns to produce relevant, accurate documentation.

How Sweet! CLI Generates Documentation

Sweet! CLI uses a session‑based AI agent that can:

  1. Analyze your codebase – read source files, understand relationships, and identify public interfaces
  2. Extract meaningful insights – infer purpose, usage patterns, and edge cases from the code
  3. Generate human‑readable documentation – produce clear explanations, examples, and diagrams
  4. Adapt to your team’s style – learn from existing documentation to match tone and structure

You interact with the documentation generator using natural‑language commands:

$ sweet "Generate a README for this project"

$ sweet "Write API documentation for the UserService class"

$ sweet "Create inline comments for all public methods in auth.js"

Step‑by‑Step: Automating Documentation with Sweet! CLI

1. Install Sweet! CLI

If you haven’t already, install Sweet! CLI:

$ pip install sweet-cli

2. Start a Documentation Session

Navigate to your project and start a session focused on documentation:

$ cd /path/to/your/project
$ sweet "Generate documentation for the billing module"

Sweet! CLI will read your project and prepare to generate docs.

3. Request Specific Documentation

Once the session is active, ask for the type of documentation you need:

> Write a comprehensive README with installation, usage, and API examples

Or target a specific component:

> Generate OpenAPI spec for all REST endpoints in app/controllers/

4. Update Existing Documentation

Keep docs in sync with code changes:

$ sweet "Update the API docs to reflect the new pagination parameters"

5. Generate Diagrams and Visuals

Sweet! CLI can also generate architecture diagrams in Mermaid or PlantUML format by describing them in text:

$ sweet "Generate a Mermaid sequence diagram for the user registration flow"

Real‑World Examples

Example 1: Project README

Generate a complete README for a Node.js project:

$ sweet "Create a README.md with project description, installation, usage, API reference, contributing guidelines, and license section"

Sample output (excerpt):

# Billing Service API
A microservice for handling subscription billing, invoicing, and payment processing.

## Installation
1. Clone the repository: `git clone https://github.com/yourorg/billing-service`
2. Install dependencies: `npm install`
3. Set environment variables (see `.env.example`)
4. Run migrations: `npm run db:migrate`
5. Start the server: `npm start`

## API Endpoints
### `POST /api/subscriptions`
Creates a new subscription.

**Request body:**
```json
{
  "plan_id": "premium_monthly",
  "customer_id": "cus_123"
}
```

**Response:**
```json
{
  "id": "sub_abc",
  "status": "active",
  "current_period_end": "2025-02-10T00:00:00Z"
}
```
…

Example 2: Inline Comments for a Python Module

Add docstrings to a legacy Python module:

$ sweet "Add Google‑style docstrings to all functions in utils/data_cleaner.py"

Before:

def normalize_text(text):
    return text.lower().strip()

After:

def normalize_text(text):
    """Normalize text by converting to lowercase and stripping whitespace.

    Args:
        text (str): Input text to normalize.

    Returns:
        str: Normalized text in lowercase with leading/trailing whitespace removed.

    Example:
        >>> normalize_text('  Hello WORLD  ')
        'hello world'
    """
    return text.lower().strip()

Example 3: API Documentation for a TypeScript Service

Generate typed API documentation for a service class:

$ sweet "Create a Markdown API reference for UserService with method signatures, parameters, return types, and examples"

Integrating Documentation Generation into Your Workflow

Pre‑commit Hook

Ensure documentation stays updated by generating it automatically before each commit:

#!/bin/bash
# pre‑commit-docs.sh
sweet "Check if any public methods are missing docstrings and add them"
sweet "Update the CHANGELOG.md with recent commits"
git add CHANGELOG.md

CI/CD Pipeline

Add a documentation‑generation step to your CI pipeline to publish updated docs on each release:

# .github/workflows/docs.yml
name: Generate Documentation
on:
  push:
    branches: [main]
jobs:
  docs:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v3
      - uses: actions/setup-python@v4
        with:
          python-version: '3.11'
      - run: pip install sweet-cli
      - run: sweet "Generate full API documentation"
      - run: sweet "Update README with latest release notes"
      - uses: peaceiris/actions-gh-pages@v3
        with:
          github_token: ${{ secrets.GITHUB_TOKEN }}
          publish_dir: ./docs

Best Practices for AI‑Generated Documentation

  1. Review generated docs – AI can make mistakes; always verify accuracy and clarity.
  2. Provide examples – Include real‑world usage examples in your prompts for better output.
  3. Maintain a style guide – Share your preferred documentation style with Sweet! CLI so it can adhere to it.
  4. Combine with human touch – Use AI for the heavy lifting, then refine for nuance and tone.
  5. Automate updates – Set up hooks or CI jobs to keep documentation synchronized with code changes.

Comparison with Other Documentation Tools

Tool Strengths Limitations Sweet! CLI Advantage
Swagger/OpenAPI Standardized API spec, UI generation Manual upkeep, limited to APIs Automatically infers endpoints, generates spec from code
JSDoc/TypeDoc Language‑specific, integrates with IDEs Requires manual annotations, no AI understanding Can add missing annotations automatically
Read the Docs Hosting, versioning, search Separate platform, manual doc writing Generates content directly from your codebase
GitHub Copilot Inline suggestions Limited to small snippets, no holistic docs Produces complete, structured documentation

Conclusion

AI‑powered documentation generation is no longer a luxury—it’s a practical necessity for teams that want to maintain high‑quality, up‑to‑date docs without sacrificing development velocity. Sweet! CLI brings this capability into your terminal, offering deep codebase understanding and tailored output that generic tools can’t match.

By automating repetitive documentation tasks, you free your team to focus on building software, while ensuring that your documentation stays accurate, comprehensive, and useful.

Pro Tip: Sweet! CLI learns from your existing documentation. Feed it a few well‑written examples, and it will emulate your team’s style and depth in all future generations.

Next Steps