All prompts

Design a unified skill package management strategy for AI coding assistants, enabling 'write once, sync everywhere' to tools like Claude Code, Cursor, and Codex.

Input your use case scenario, and AI will help you filter, evaluate, and compare the most suitable skill packages from the vast Agent skill ecosystem, providing installation advice and integration plans.

Describe your voice AI product idea in one sentence, and automatically generate a complete PRD document including technology selection, architecture design, and interaction flows.

Help developers quickly evaluate and select suitable Text-to-Speech (TTS) technology solutions, comparing open-source and commercial options across quality, latency, multi-language support, and other dimensions.

Describe your repetitive workflow in natural language to automatically generate executable automation scripts (supporting n8n/Zapier/Python/Shell).

Design headless browser automation solutions for AI Agents to bypass anti-scraping detection, including fingerprint masking, request pattern optimization, and detection evasion strategies.

Assess whether any open-source project is suitable for agentization and generate specific transformation plans and technical roadmaps.

Help developers compare and evaluate different AI code sandbox execution solutions (containers, microVMs, embedded interpreters) and output a structured selection report.

Automatically generate multi-model routing rules for your AI coding assistant based on your use case and budget: use cheaper models for simple tasks and stronger models for complex ones, saving up to 70% in costs.

When multiple AI coding Agents modify the same code repository in parallel, automatically detect potential conflict areas and generate optimal merge strategies and conflict resolution solutions.

Analyzes token usage patterns of AI coding agents and generates optimized CLI proxy tool configurations (e.g., rtk) to achieve 60-90% token savings.

Given a GitHub repository URL, automatically analyze its tech stack, architectural patterns, core modules, and data flow to generate a structured technical architecture document.

Describe your desired cloud infrastructure architecture in natural language; the AI automatically generates production-grade Terraform code, including best practices and security configurations.

Transform fuzzy requirements into reproducible, verifiable AI code execution contracts. Suitable for developers using coding agents such as Claude Code/Codex/Cursor, solving prompt uncertainty issues.

Based on guest background and podcast topics, it automatically generates a deep, layered list of interview questions, including icebreakers, core topics, controversial questions, and closing sessions.

Design streaming UI rendering solutions for LLM applications, plan component libraries, define generative UI language formats, and optimize token efficiency

Design an AI-based system for real-time transcription, summary generation, and automatic extraction of action items from meeting audio.

Analyze open-source project growth data, identify key growth milestones, and generate actionable recommendations for optimizing promotion strategies.

Quickly extract core technical highlights of open-source projects to generate a one-page summary suitable for technical blogs or social media sharing.

Input a repository link to automatically analyze project architecture and generate Mermaid dependency diagrams, complexity heatmaps, and onboarding reading routes.

Help you evaluate and select the most suitable open-source speech synthesis/cloning solution, providing comprehensive comparative analysis across tech stacks, deployment costs, audio quality, and multilingual support.

Paste a batch of GitHub Issue titles and descriptions; the AI automatically classifies them by type and assigns priorities (P0-P3), outputting a structured table.

Systematically compare mainstream Agent sandbox solutions (Container Sandbox vs. WebAssembly Isolation vs. V8 Isolate), providing selection recommendations and architecture design documentation.

Input your voice application requirements to generate a complete technical solution for multi-language TTS voice cloning, including model selection, deployment architecture, and code examples.

Design a rigorous A/B test experiment plan for your LLM application, including sample size calculation, evaluation metric definition, statistical significance testing, and result visualization code.

Manage your AI coding agents as true team members—assign tasks, track progress, and accumulate skills.

Build a financial time series analysis framework using AI, combining foundation models for market trend prediction and risk assessment.

Design a fully local document semantic search system from scratch, supporting multi-format documents, vector retrieval, and natural language Q&A.

Helps convert various documents (PDF, Word, Excel, etc.) into structured Markdown, performing intelligent cleaning and summary extraction to prepare data for RAG knowledge bases and LLM analysis.

Design a comprehensive stress testing plan for an AI Agent's memory system, evaluating retrieval accuracy, forgetting curves, context window utilization, and cross-session consistency.

Describe your backend requirement in one sentence, and automatically generate complete TypeScript/Node.js backend API code, including routes, database Schema, validation, and tests.

Input a document or topic to automatically generate a professional PPT outline and content, including layout suggestions and speaker notes.

An AI analysis prompt for bioinformatics and drug R&D personnel, helping to understand protein structures, predict functional sites, and identify drug targets.

Guide large language models to improve output quality during inference through adaptive computation strategies, leveraging test-time scaling techniques for better responses.

Transform dry open-source project READMEs into engaging, well-structured documentation to increase project visibility and star growth.

Create an AI learning tutor that adapts to student levels, supporting Socratic questioning and knowledge graph tracking.

Design a complete multimodal content moderation solution for AI applications, covering safety and compliance strategies for text, images, video, and audio.

Helps you build a local text-to-speech environment from scratch, supporting multilingual and multi-voice cloning.

Unified management of multiple AI coding agents, assigning tasks, tracking progress, and accumulating skills like a team manager.

Generate a complete product plan for a real-time voice AI dialogue system with one click, including technology stack selection, architecture design, and latency optimization strategies.

Design intuitive visual monitoring interfaces for multi-agent systems, making the status of AI Agents clear at a glance.

Input game genre and core gameplay mechanics to automatically generate a complete Game Design Document, including system design, numerical frameworks, level structures, and technical solutions.

Convert natural language scene descriptions into technical parameters and camera path planning suitable for 3D Gaussian Splatting rendering.

Generate a secure sandbox execution plan for AI Agents based on capability isolation, including permission policies, resource limits, and escape prevention.

Input agent execution logs or error messages to automatically analyze workflow bottlenecks, reasons for tool call failures, and provide fix suggestions and optimization plans. Suitable for frameworks like LangChain, CrewAI, and AutoGen.

Use Gene Expression Programming (GEP) methods to design AI Agent evolution strategies, including gene encoding, fitness functions, and evolutionary operators.

Enables AI to act as an autonomous task planner, decomposing complex goals into executable sub-tasks, automatically planning dependencies, and executing them step-by-step. Suitable for models like ChatGPT/Claude.

Input a one-sentence requirement description to automatically generate a complete system architecture Mermaid diagram, including components, data flows, and deployment suggestions.