All prompts

Automatically plans the skill modules, toolchains, and execution flows required by an AI Agent based on task descriptions.

A prompt for local deployment and debugging of Vision Language Models (VLMs) designed specifically for Apple Silicon Mac users, based on the MLX framework.

Design multi-tool parallel scheduling strategies for AI Agents, including task decomposition, tool selection, result aggregation, and exception fallback mechanisms.

Enter project information and automatically generate a README in Chinese, English, and Japanese, including badges, installation instructions, usage examples, and other complete structures.

Automatically analyze Web application code, identify attack vectors, and generate reproducible vulnerability exploitation plans.

Help researchers systematically reproduce experiments from AI papers, providing end-to-end guidance from environment setup to result verification.

Help developers quickly configure MCP Server to connect to databases, providing structured data access capabilities for AI Agents.

Design AI chatbot architectures supporting multiple platforms like WeChat, Telegram, and Discord, including message routing, context management, and plugin systems.

Expert consultant for designing and building full-stack serverless applications using Cloudflare Workers, D1, R2, KV, and other edge computing services.

Uses AI to analyze time series data, generating forecasting reports and visualization suggestions

Helps design reinforcement learning training schemes for AI Agents, including reward function design, trajectory sampling strategies, and automatic prompt optimization, applicable to any Agent framework.

Generate performance benchmark reports for LLM inference on edge devices, covering latency, throughput, memory usage, and quantization strategy comparisons.

Generate a comprehensive performance tuning checklist and optimization suggestions for locally deployed on-device large language models.

Design AI data pipelines for processing images, audio, video, and structured data, suitable for large-scale data engineering scenarios.

Breaks down penetration testing targets into automated sub-task chains, supporting the full process from information gathering and vulnerability scanning to exploitation and report generation.

Input your service description to automatically generate a complete code framework for a Model Context Protocol Server.

Help compress long conversations/documents to fit within the LLM context window, preserving key information and reducing token consumption.

Design robust error handling, automatic retry, and graceful degradation strategies for AI Agent systems.

Help you describe multi-agent collaboration scenarios in natural language, automatically generating a complete workflow orchestration plan, including agent role definitions, message routing, fault tolerance strategies, and human-in-the-loop nodes.

Generates a complete local LLM fine-tuning plan based on hardware conditions and task requirements, including data preparation, training configuration, and deployment.

Generate local LLM deployment plans for Mac users, including model selection, quantization strategies, MLX/llama.cpp configurations, and performance tuning suggestions.

Automatically decomposes complex tasks into multiple professional Agent sub-tasks, generating executable orchestration plans and code frameworks.

Analyzes system prompts of any AI product, extracting design patterns, security mechanisms, and functional architecture to help you understand how top-tier AI products design their prompts.

Automatically generates best practice configurations for Claude Code based on your project type, including CLAUDE.md, sub-Agent definitions, custom commands, and skill modules.

Automatically analyze invoices, receipts, and bank statements, archive them by category, and generate expense reports.

Transforms basic READMEs into professional, visually appealing versions that attract stars, supporting bilingual (Chinese/English) output.

Describe the automation process you want in natural language, and AI helps break it down into executable Agent workflow steps.

Architectural guidance, concurrency patterns, and performance optimization advice for building AI Agents and LLM applications in Go.

Design and build a local-first document semantic search system supporting intelligent retrieval of meeting minutes, notes, and knowledge bases.

Use AI for technical analysis of cryptocurrencies and stocks, including Bollinger Bands, candlestick pattern recognition, and multi-exchange screening.

Analyze your AI Agent workflow to identify token waste points, generate context compression plans, and help you save money and improve efficiency.

Helps design voice AI product solutions, covering the entire process from requirement analysis to technology selection to user experience

Paste agent runtime logs to AI to automatically identify failure reasons, provide fix suggestions, and retry strategies

Diagnose your efficiency in using AI coding assistants (Cursor/Copilot/Claude Code, etc.) and provide optimization suggestions.

Design the optimal local RAG/semantic search architecture based on your data type and scale.

Describe a scene to generate detailed anime-style prompts suitable for tools like Midjourney/SD.

Input basic information about an open-source project to automatically generate a high-quality bilingual (Chinese + English) README, suitable for international promotion.

Rapidly designs computer vision solutions based on business requirements, including model selection and deployment architecture.

Input a GitHub project link, and the AI will summarize its core value, applicable scenarios, and potential risks in one sentence.

Generate Compound Engineering best practice configurations for coding Agent projects to improve multi-Agent collaborative code quality.

Design role assignment, communication protocols, and task orchestration schemes for multi-agent collaboration systems.

Design and write custom skill files for AI coding assistants like Claude Code and Codex to extend Agent capabilities.

Enter your GitHub repository information to automatically generate a professional project weekly report including progress, issues, and plans for next week

Helps you design task scheduling strategies for multi-agent parallel coding, resolving code conflicts, resource competition, and other issues.

Analyze issues in open-source project READMEs and generate optimized versions to improve discoverability and developer conversion rates.

Conduct a comprehensive security audit of an AI application's System Prompt, detect injection vulnerabilities and information leakage risks, and generate hardening suggestions and rewritten versions.

Design comprehensive error recovery and self-healing strategies for AI Agent systems, including retry mechanisms, degradation plans, and alerting rules.

Generate a comprehensive performance optimization checklist for deploying AI models on edge/on-device scenarios, covering model compression, inference acceleration, and resource management.