All prompts

Describe requirements in natural language; AI automatically breaks them down into subtasks for multiple coding agents and generates a progress tracking dashboard.

Analyze whether text or images contain AI-generated watermarks (such as SynthID) and provide a detection report with confidence assessment.

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

Have AI review your code against Rust performance best practices, covering key dimensions such as memory allocation, concurrency, and zero-copy patterns.

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

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

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

Input a topic and style to automatically generate a complete short video script, including storyboard descriptions, dialogue, duration, and visual cues, suitable for Douyin/Xiaohongshu/YouTube Shorts.

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

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.

Quickly assess the technical value, community health, and potential adoption opportunities of this week's trending open-source projects based on GitHub Trending data.

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.

Generate detailed 3D scene specifications from natural language descriptions, compatible with mainstream 3D generation frameworks such as NeRF, Gaussian Splatting, and diffusion models.

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

Design breakpoint saving, state snapshot, and automatic recovery mechanisms for AI Agents executing multi-step long tasks to prevent progress loss due to task interruptions.

Automatically detect personally identifiable information (PII) in text, code, and documents, generating masking plans and GDPR/Personal Information Protection Law compliance recommendations.

Automatically generate complete Python data processing pipeline code based on natural language descriptions of data cleaning needs, supporting frameworks like Pandas and Polars.

Based on historical project data, community activity, and external events, predict the Star growth trend of open-source projects, generating community operation growth models and strategic recommendations.

Transform repetitive terminal operations described in natural language into reusable automated scripts supporting Bash/Zsh/Fish, including error handling and logging.

Transform vague project requirements into structured Agent team task assignment schemes, including role definitions, task breakdowns, dependencies, and acceptance criteria. Suitable for multi-agent collaboration tools such as Squad and Claude Agent Teams.

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.

Generate complete product design documentation for multimodal AI Agent desktop applications, covering core capabilities such as GUI operations, browser automation, and MCP tool integration.

For CI/CD systems like GitHub Actions, a comprehensive security hardening checklist is automatically generated, covering key security areas such as supply chain attack protection, key management, and permission minimization.

Helps review React code generated by AI coding agents, detects common anti-patterns (unnecessary re-renders, closure traps, state management errors, etc.), and provides fixing suggestions.

Analyze contributor structure, community activity, and health metrics of GitHub open-source projects to generate visual reports.

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

Track and plan the capability evolution path of AI Agents after deployment, including skill acquisition, memory optimization, and self-improvement strategies.

Automatically generate multi-LLM model routing strategies based on task type, cost budget, and latency requirements to help developers intelligently distribute requests across different models.

Design fine-grained sandbox security policies for AI Agent applications, including file system, network, and process permission controls, suitable for WebAssembly isolation and containerized deployment scenarios.

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.

Help developers evaluate and select the most suitable LLM inference acceleration technologies, including speculative decoding, quantization, and KV Cache optimization.

Design multilingual speech synthesis and cloning solutions based on the latest open-source TTS technologies, covering voice design, emotion control, and streaming output.

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.

Describe your AI Agent workflow to automatically generate Mermaid flowchart code, which can be directly pasted into documents for rendering.

Systematically evaluate the strategy logic, risk control mechanisms, and drawdown tolerance of your AI autonomous trading system, generating a structured pre-launch checklist.

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.

Design the task workflow for an automation agent, including deployment, monitoring, fault recovery, and scaling strategies.

Input project requirements to automatically generate a multi-agent collaboration task board, including task assignment, dependencies, and priority sorting.

Decompose complex development requirements into independently executable sub-tasks and generate detailed agent instructions for each, compatible with multi-agent coding platforms like Multica and Claude Code.

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.

Instruct the AI Agent to automatically loop through and execute all items in the PRD until completion. Suitable for autonomous development scenarios with coding agents like Claude Code or Codex.

Analyze whether text or images contain AI-generated watermarks (such as Google SynthID) and explain the detection principles and academic discussions on evasion methods.

Generate reusable YAML workflow definitions for AI coding projects, making the AI coding process repeatable and auditable.

Describe your desired 3D scene in natural language, and AI will generate a detailed scene specification document usable in Blender, Unity, or other 3D tools.

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

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.