readme-updater

This skill helps maintain a consistent and up-to-date README.md file for your repository. It automates the process of extracting information from the project's codebase to ensure documentation is always in sync with implementation.

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Install skill "readme-updater" with this command: npx skills add prulloac/git-blame-vsc/prulloac-git-blame-vsc-readme-updater

README Updater

This skill helps maintain a consistent and up-to-date README.md file for your repository. It automates the process of extracting information from the project's codebase to ensure documentation is always in sync with implementation.

Features

  • Project Overview Synchronization: Updates the project description and features list based on the latest implementation.

  • Installation & Setup Tracking: Automatically detects project type (Node.js, Python, Rust, etc.) and updates setup/installation commands.

  • Usage Examples Generator: Scrapes code examples from test suites or examples/ directory and integrates them into the README.

  • Version and Changelog Linking: Keeps the current version and links to the CHANGELOG.md updated.

  • Dependency Visualization: Optionally generates or updates a list of main dependencies or a simple architecture overview.

Workflow

Step 1: Analyze the Workspace

Before updating, the agent must gather context about the project's current state.

  • Check root files: Look for package.json , requirements.txt , Cargo.toml , go.mod , setup.py , etc.

  • Determine project type: Identify the primary language and frameworks used

  • Locate entry points: Find the main script or binary that users will interact with

  • Extract metadata: Parse version, name, description from configuration files

  • Discover dependencies: List main dependencies and development dependencies

  • Find examples: Look for examples/ , demo/ , or test/ directories with usage samples

Step 2: Identify Update Scope

Determine what needs updating:

  • README exists? If not, create from standard template

  • Which sections? Analyze current README and identify stale sections

  • Version changed? Compare README version with actual version in package.json , Cargo.toml , etc.

  • Features updated? Check if new features need to be documented

  • Dependencies changed? Verify dependency list is current

  • Examples stale? Check if example code matches current API

Step 3: Extract Current Information

Build a profile of the project:

  • Project metadata: Name, description, version, repository URL

  • Installation instructions: Commands needed to set up the project

  • Usage examples: Working code examples from tests or examples directory

  • Configuration: Environment variables, config files, custom options

  • Dependencies: List of critical or main dependencies

  • Supported platforms: OS, Node versions, Python versions, etc.

Step 4: Update README Content

For each section that needs updating:

Project Overview (Top section):

  • Update project title and description

  • Add/update feature list

  • Add badges (downloads, version, license, build status)

Installation Section:

  • Update prerequisite list

  • Provide correct install commands for detected project type

  • Include multiple installation methods if applicable

Usage Section:

  • Add quick start example

  • Update command syntax if changed

  • Include common flags or options

Examples Section:

  • Extract or update code examples

  • Ensure examples actually work with current version

  • Add multiple usage scenarios

Configuration Section:

  • Document all environment variables

  • List configuration file locations and formats

  • Provide example configurations

Footer Sections:

  • Update Contributing link if CONTRIBUTING.md exists

  • Keep License reference current

  • Update version and changelog links

Step 5: Validation & Verification

Always verify the README's correctness after an update:

  • ✅ All links are valid and pointing to correct files

  • ✅ All commands are correct, tested, and up-to-date

  • ✅ Installation steps match actual project requirements

  • ✅ Code examples are syntactically correct and runnable

  • ✅ Version numbers match across README and package.json /manifest files

  • ✅ Tone remains consistent with original documentation

  • ✅ No broken markdown syntax (proper formatting)

  • ✅ Badge URLs and shields are current

Step 6: Summary & Report

Generate comprehensive update summary showing:

  • What sections were modified

  • What metadata was discovered and used

  • Any detected issues or recommendations

  • Before/after comparison of key sections

Concrete Examples

Example 1: Node.js Project Update

Project Type Detected: Node.js / TypeScript Files Scanned: package.json (v2.1.0), README.md (old, v1.5.0)

Before:

my-awesome-cli

Command-line tool for development tasks.

Installation

npm install -g my-awesome-cli

Usage

my-awesome-cli help

Features

- Task automation

**After:**
```markdown
# my-awesome-cli

[![npm version](https://img.shields.io/npm/v/my-awesome-cli.svg)](https://npmjs.org/package/my-awesome-cli)
[![npm downloads](https://img.shields.io/npm/dm/my-awesome-cli.svg)](https://npmjs.org/package/my-awesome-cli)
[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://github.com/user/my-awesome-cli/blob/main/LICENSE)

Advanced command-line tool for automating development workflows with TypeScript support and interactive configuration.

## Features

- **Task Automation**: Easily define and run complex development tasks
- **TypeScript Support**: First-class TypeScript configuration and plugins
- **Interactive Config**: Interactive setup wizard for project configuration
- **Watch Mode**: Automatic task re-run on file changes
- **Plugin System**: Extend functionality with custom plugins

## Installation

### Prerequisites

- Node.js 16.0 or higher
- npm 7.0 or higher (or yarn/pnpm)

### Quick Start

```bash
# Install globally
npm install -g my-awesome-cli

# Or use npx (no installation required)
npx my-awesome-cli --version

Usage

Basic Commands

# Show help
my-awesome-cli help

# Initialize project
my-awesome-cli init

# Run a task
my-awesome-cli run build

# Watch mode
my-awesome-cli run build --watch

Examples

Initialize a new project:

my-awesome-cli init
# Follow the interactive prompts to set up your project

Create a custom task:

# Edit .myawesomerc.json
{
  "tasks": {
    "build": {
      "commands": ["npm run compile", "npm run bundle"]
    }
  }
}

Run with TypeScript:

my-awesome-cli run build --ts

Configuration

Environment Variables

- MY_AWESOME_CONFIG
: Path to custom config file (default: .myawesomerc.json
)

- MY_AWESOME_LOG_LEVEL
: Logging level (debug, info, warn, error) (default: info)

Config File Format

Create .myawesomerc.json
 in your project root:

{
  "version": "1.0",
  "tasks": {
    "build": {
      "commands": ["npm run compile"]
    },
    "test": {
      "commands": ["npm test"]
    }
  },
  "plugins": ["@my-awesome-cli/typescript"]
}

Contributing

Contributions are welcome! Please read CONTRIBUTING.md for details.

License

This project is licensed under the MIT License - see LICENSE for details.

**Update Summary:**

═══════════════════════════════════════════════════════════
README UPDATE SUMMARY
═══════════════════════════════════════════════════════════

Project: my-awesome-cli
Type: Node.js / TypeScript
Status: ✅ SUCCESSFULLY UPDATED

───────────────────────────────────────────────────────────
CHANGES MADE
───────────────────────────────────────────────────────────

✅ Version Updated
Old: v1.5.0 → New: v2.1.0
Source: package.json

✅ Badges Added

- npm version badge

- npm downloads badge

- MIT license badge

✅ Features Section Expanded
Old: 2 features → New: 5 features with descriptions

✅ Installation Section Updated

- Added prerequisites section

- Included npx alternative

- Clearer quick start

✅ Usage Section Enhanced

- Reorganized commands

- Added watch mode flag

- TypeScript examples

✅ Examples Section Created

- Project initialization example

- Custom task configuration

- TypeScript usage example

✅ Configuration Section Added

- Environment variables documented

- Config file format with example

- Plugin system noted

✅ Contributing & License Links Updated

- Verified files exist

- Links are current

───────────────────────────────────────────────────────────
METADATA EXTRACTED
───────────────────────────────────────────────────────────

Name: my-awesome-cli
Version: 2.1.0
Description: Advanced command-line tool for automating development workflows...
Main Dependencies:

- commander@^11.0.0

- chalk@^5.0.0

- ora@^7.0.0

Dev Dependencies: @types/node, typescript, jest

Entry Point: bin/cli.ts

Supported Node Versions: >=16.0.0

═══════════════════════════════════════════════════════════

### Example 2: Python Project Update

**Project Type Detected**: Python / PyPI Package
**Files Scanned**: `pyproject.toml` (v0.3.0), `README.md` (v0.2.0)

**Before:**
```markdown
# my-python-lib

Python library for data processing.

## Installation

pip install my-python-lib

## Usage

from my_python_lib import process
result = process(data)

After:

# my-python-lib

[![PyPI version](https://img.shields.io/pypi/v/my-python-lib)](https://pypi.org/project/my-python-lib/)
[![Python 3.8+](https://img.shields.io/badge/python-3.8+-blue.svg)](https://www.python.org/downloads/)
[![License: Apache 2.0](https://img.shields.io/badge/License-Apache%202.0-blue.svg)](LICENSE)

High-performance data processing library for machine learning and data science workflows.

## Features

- **Fast Processing**: Optimized algorithms for large datasets
- **Type Hints**: Full type annotations for better IDE support
- **Async Support**: Built-in async/await support for concurrent operations
- **Comprehensive Logging**: Detailed logging for debugging and monitoring
- **Pandas Compatible**: Works seamlessly with pandas DataFrames

## Installation

### Requirements

- Python 3.8 or higher
- pip or conda

### From PyPI

```bash
pip install my-python-lib

From Conda

conda install -c conda-forge my-python-lib

Development Installation

git clone https://github.com/user/my-python-lib.git
cd my-python-lib
pip install -e ".[dev]"

Quick Start

from my_python_lib import DataProcessor

# Initialize processor
processor = DataProcessor(batch_size=1000)

# Process data
results = processor.transform(data, normalize=True)

# Get statistics
stats = processor.get_stats()
print(f"Processed {stats['count']} items in {stats['time']:.2f}s")

Usage Examples

Basic Data Processing

import pandas as pd
from my_python_lib import DataProcessor

# Load data
df = pd.read_csv('data.csv')

# Create processor
processor = DataProcessor()

# Process
result = processor.fit_transform(df)

Async Processing

import asyncio
from my_python_lib import AsyncDataProcessor

async def process_large_dataset():
    processor = AsyncDataProcessor(workers=4)
    results = await processor.transform(large_data)
    return results

# Run async processor
asyncio.run(process_large_dataset())

Custom Transformations

from my_python_lib import DataProcessor, transforms

processor = DataProcessor(
    transforms=[
        transforms.Normalize(),
        transforms.Impute(strategy='mean'),
        transforms.FeatureScale()
    ]
)

Configuration

Environment Variables

- MY_PYTHON_LIB_LOG_LEVEL
: Logging level (DEBUG, INFO, WARNING, ERROR) (default: INFO)

- MY_PYTHON_LIB_WORKERS
: Number of worker threads (default: CPU count)

- MY_PYTHON_LIB_CACHE_DIR
: Directory for caching processed data (default: ~/.cache/my-python-lib)

Configuration via Code

from my_python_lib import config

config.set_log_level('DEBUG')
config.set_workers(8)
config.enable_caching(cache_dir='/tmp/cache')

API Reference

See API_REFERENCE.md for complete API documentation.

Contributing

Contributions welcome! See CONTRIBUTING.md for guidelines.

License

Licensed under Apache License 2.0 - see LICENSE for details.

**Update Summary:**

═══════════════════════════════════════════════════════════
README UPDATE SUMMARY
═══════════════════════════════════════════════════════════

Project: my-python-lib
Type: Python / PyPI Package
Status: ✅ SUCCESSFULLY UPDATED

───────────────────────────────────────────────────────────
CHANGES MADE
───────────────────────────────────────────────────────────

✅ Version Updated
Old: v0.2.0 → New: v0.3.0
Source: pyproject.toml

✅ Badges Added

- PyPI version badge

- Python 3.8+ requirement badge

- Apache 2.0 license badge

✅ Features Section Expanded
Old: 1 feature → New: 5 features with descriptions

✅ Installation Section Restructured

- Added requirements section

- PyPI installation method

- Conda installation method

- Development installation steps

✅ Quick Start Section Added

- Simple example code

- Realistic use case

✅ Usage Examples Section Expanded

- Basic data processing example

- Async processing example

- Custom transformations example

✅ Configuration Section Added

- Environment variables documented

- Code-based configuration examples

✅ API Reference Link Added

- Points to docs/API_REFERENCE.md

───────────────────────────────────────────────────────────
METADATA EXTRACTED
───────────────────────────────────────────────────────────

Name: my-python-lib
Version: 0.3.0
Description: High-performance data processing library for machine learning...
Python Version: >=3.8
License: Apache-2.0

Main Dependencies:

- numpy>=1.20.0

- pandas>=1.3.0

Dev Dependencies:

- pytest

- black

- mypy

- sphinx

PyPI URL: https://pypi.org/project/my-python-lib/

═══════════════════════════════════════════════════════════

## Output Format Example

When the skill completes an update, it should provide a summary of changes:

### README Update Summary

- ✅ **Installation**: Updated installation section with new Python requirements
- ✅ **Usage**: Added async processing and custom configuration examples
- ✅ **Version**: Updated from v0.2.0 to v0.3.0 to match `pyproject.toml`
- ✅ **Features**: Expanded from 1 to 5 features with detailed descriptions
- ✅ **Badges**: Added PyPI, Python version, and license badges
- ✅ **Configuration**: Added environment variables and code-based setup guide

## References

- [README Template](references/readme_template.md) - Standard layout for project documentation.
- [Project Discovery Patterns](references/discovery_patterns.md) - How to find project info across different languages.

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