Added documentation

.gitignore

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 .env
 venv/
-__pycache__/
+__pycache__/
+.DS_Store

DOCUMENTATION.md

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+# PROMPT-TOOL 🤖
+
+## Overview
+Prompt-tool is a Python-based utility designed to enhance and structure prompts for Large Language Models (LLMs) and AI agents, especially for coding and developer productivity tasks. It provides a Gradio web interface and an MCP server endpoint for generating context-aware, high-quality prompts, optionally leveraging available tools in the host environment.
+
+## Features
+- **Prompt Engineering**: Generates detailed, structured prompts for LLMs, focusing on coding tasks.
+- **Tool Awareness**: Can incorporate available tools (e.g., Playwright) into prompt instructions.
+- **Multiple Models**: Supports different LLM models (gpt-4.1-nano, gpt-4.1-mini) for basic and advanced prompt generation.
+- **Web Interface**: Gradio-based UI for interactive prompt generation.
+- **MCP Server Integration**: Exposes prompt-tool as an MCP tool for programmatic access.
+- **Customizable Instructions**: Uses a configurable prompt template (see `prompts/coding.txt`).
+
+## Installation
+1. Clone the repository and navigate to the `work/prompt-tool` directory.
+2. Install dependencies:
+   ```bash
+   pip install -r requirements.txt
+   ```
+3. Create a `.env` file with your OpenAI API key:
+   ```env
+   OPENAI_API_KEY=your_openai_api_key_here
+   ```
+
+## Usage
+### Gradio Web Interface
+Run:
+```bash
+python mcp_gradio.py
+```
+- Enter your prompt, select the model (A: advanced, B: basic, N: no tooling), and specify available tools (comma-separated).
+- Click "Generate" to receive an enhanced prompt.
+
+> **Note:** When running the Gradio interface, an MCP server is also created and exposed automatically.
+
+### MCP Server
+Run:
+```bash
+python mcp_server.py
+```
+This exposes the prompt-tool as an MCP tool endpoint for integration with other MCP-compatible systems.
+
+### Programmatic Usage
+You can import and use the core functions in your own Python scripts:
+```python
+from generator import prompt_tool
+result = prompt_tool("Your prompt here", tool="A", tools="playwright"
+```
+
+## Architecture
+- **generator.py**: Core logic for prompt generation, model selection, and OpenAI API interaction.
+- **mcp_gradio.py**: Gradio web interface for interactive use.
+- **mcp_server.py**: MCP server exposing the prompt-tool as an endpoint.
+- **prompts/coding.txt**: Template and guidelines for prompt generation.
+- **requirements.txt**: Python dependencies.
+
+## Prompt Template
+The prompt-tool uses a template (`prompts/coding.txt`) that enforces best practices in prompt engineering, such as specificity, structured frameworks, tool specification, output format, and constraints.
+
+This allows the user to use prompt-tool for whatever they want—this means that the tool can be tailored for tasks other than coding just by changing the template and a couple of lines of code.
+
+## Cursor integration
+
+In order to use prompt-tool in Cursor, you need to add the following to your `.cursor/mcp.json` file:
+
+```json
+    {
+    "mcpServers": {
+        "prompt-tool": {
+        "url": "your_mcp_server_url"
+        }
+    }
+    }
+```
+
+## Development & Contribution
+- Exclude `.env`, `venv/`, and `__pycache__/` from version control (see `.gitignore`).
+- To contribute, fork the repository, create a feature branch, and submit a pull request.
+- Please ensure code is well-documented and tested.
+
+## License
+MIT License
+
+---
+*This documentation will be updated to include images and diagrams in the future.*

mcp_gradio.py

@@ -9,7 +9,7 @@ def main():
         gr.Markdown("# Prompt tool demo")
         prompt = gr.Textbox(label="Prompt", placeholder="Enter your prompt here...")
         tool = gr.Dropdown(choices=["A", "B", "N"], value="A", label="Tool", info="Select the tool type")
-        tools = gr.Textbox(label="Tools (comma-separated)", placeholder="e.g. playwright, websearch", value="playwright")
+        tools = gr.Textbox(label="Tools (comma-separated)", placeholder="e.g. playwright, websearch")
         output = gr.Textbox(label="Output")
         btn = gr.Button("Generate")