Software Engineering

Step-by-Step Agentic CLI Coding Tool Development Plan Generator

Name: Step-by-Step Agentic CLI Coding Tool Development Plan Generator
Author: Claude Directory

Claude Directory February 6, 2026

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This prompt generates a comprehensive Markdown roadmap for building professional, interactive, agentic CLI coding tools with stunning TUIs, inspired by Claude Code and Aider. Customize placeholders and feed to an AI for an executable build plan.

Prompt

You are an expert software architect and prompt engineer with deep knowledge of building high-quality CLI tools in terminal environments. Your task is to create a comprehensive, step-by-step development plan in Markdown format for constructing an agentic coding CLI tool. This tool must be:

- **Agentic**: Autonomous, multi-step reasoning, tool-using AI agent for coding tasks (e.g., planning, writing, debugging, refactoring code).
- **Interactive and UX-focused**: Smooth terminal interface with no jarring transitions; user stays in flow while typing commands, editing code, or interacting with AI suggestions. Use rich terminal UI libraries for visual appeal (e.g., beautiful prompts, progress bars, syntax-highlighted previews, modal-like editors).
- **Visually stunning**: Leverage best-practice terminal UI libraries like Ink, Blessed, or Rich for Python/Node.js; ensure TUI (Text User Interface) that's comfortable, responsive, and professional.
- **Best practices**: Modular architecture, error handling, extensibility, async operations, secure API integrations (e.g., for LLMs like Claude/Anthropic, OpenAI), offline capabilities where possible, cross-platform (macOS/Linux/Windows via WSL).
- **Inspirations**: Combine Claude Code (interactive coding sessions), Crush (powerful shell-like), Aider/Cursor CLI vibes. Research and incorporate latest best practices from sources like GitHub repos (e.g., Aider, Claude-Dev, Continue.dev CLI), Terminal TUI guides (e.g., gum, choo-choo), agentic frameworks (e.g., LangChain CLI agents, AutoGen).

**Provided Research/Context**: [RESEARCH_INFO]

**Tool Specifics**:
- Name: [TOOL_NAME]
- Core Features: [KEY_FEATURES] (e.g., chat-based coding, file editing in-place, git integration, multi-agent collaboration).
- Tech Stack Preferences: [TECH_STACK] (e.g., Node.js with Ink/Zodiac, Python with Textual/Rich/PromptToolkit).
- Target: Pure CLI/TUI in terminal, no web/GUI.

Output **ONLY** a clean Markdown document (.md) with:
1. **Introduction**: Overview of the tool and high-level architecture.
2. **Prerequisites**: Setup instructions (dependencies, env vars).
3. **Step-by-Step Build Plan**: Numbered steps (20-40 detailed sub-steps), each with:
   - What to do.
   - Code snippets/examples.
   - Commands to run/test.
   - Best practices rationale.
   - Potential pitfalls/solutions.
4. **Testing & Iteration**: QA steps, edge cases.
5. **Deployment & Polish**: Packaging (npm/pipx), README, extensibility.

Make it copy-paste ready for a coding AI like Codex/GPT to execute sequentially in the terminal. Ensure steps build incrementally without breaking UX. Use [YOUR_OWN_RESEARCH] to add cutting-edge insights (e.g., latest TUI libs, agentic patterns from 2024 papers/repos).

How to Use

1. Fill placeholders: [RESEARCH_INFO] with relevant context/research; [TOOL_NAME] e.g., 'CodeAgent'; [KEY_FEATURES] e.g., 'chat coding, git integration'; [TECH_STACK] e.g., 'Python with Textual'. 2. Paste the full prompt into an AI like Claude or GPT-4. 3. Use the output Markdown plan sequentially with a coding AI/editor for incremental development. Test each step in a new terminal project.

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