docs: update repository description and topic instructions

Clarify the process for generating repository descriptions and selecting relevant topics to improve discoverability and attract potential contributors.

pyproject.toml

@@ -23,7 +23,7 @@ dependencies = [
   "transformers>=4.46.3",
   "typer>=0.13.1",
 ]
-description = "🚀 LLM CLI - A versatile command-line interface for interacting with various AI models, supporting multiple providers like DeepSeek, and offering seamless integration for AI-driven tasks."
+description = "TODO"
 name = "liblaf-llm-cli"
 readme = "README.md"
 requires-python = ">=3.12"

src/llm_cli/assets/instructions/description.md

@@ -1,7 +1,7 @@
-Analyze the codebase provided above, generate a concise, one to two-sentence description of this repository. The description should be informative and engaging to help others discover and potentially contribute to the project.
-
-**Example Description:**
+Using the details provided in the repository codebase, compose a brief and engaging description of the repository in one to two sentences. The description should include the repository's main purpose, highlight its key features, and identify its appeal to potential contributors. Aim for clarity and conciseness to effectively communicate the value of the repository.
 
+<example>
 <answer>
 🤯 Lobe Chat - an open-source, modern-design AI chat framework. Supports Multi AI Providers (OpenAI / Claude 3 / Gemini / Ollama / Azure / DeepSeek), Knowledge Base (file upload / knowledge management / RAG), Multi-Modals (Vision / TTS) and plugin system. One-click FREE deployment of your private ChatGPT / Claude application.
 </answer>
+</example>

src/llm_cli/assets/instructions/topics.md

@@ -1,18 +1,7 @@
-Based on the given codebase, identify and suggest relevant topics to enhance the repository's discoverability and appeal to potential contributors. The suggested topics should effectively represent the repository's intended purpose, subject area, possible affinity groups, or other significant attributes.
-
-**Context:**
-
-- The goal is to make the repository easier to find and understand for users and contributors.
-- Consider aspects like languages used, project type, technologies involved, and the community it serves.
-
-**Output Example:**
+Analyze the provided codebase and propose a list of up to 20 relevant topics that will enhance the repository's discoverability and attractiveness to potential contributors. Consider the intended purpose, subject area, programming language, and any unique features of the project. Ensure all topics are in lowercase, use hyphens if necessary, and contain no more than 50 characters each.
 
+<example>
 <answer>
 chat ai nextjs tts gemini openai gpt knowledge-base claude rag gpt-4 chatgpt chatglm azure-openai-api function-calling ollama dalle-3 gpt-4-vision qwen2
 </answer>
-
-**Instructions:**
-
-1. Review the codebase.
-2. Analyze the codebase details to identify core attributes.
-3. List topics that accurately classify and describe the repository.
+</example>