All prompts

Input the product name and core selling points to automatically generate launch copy suitable for both Twitter/X and Xiaohongshu, including hooks, feature highlights, CTAs, and tags.

Design a secure sandbox execution environment for AI Agents based on WebAssembly, including resource limits, permission models, and escape prevention.

Design a long-term memory system for an AI assistant based on knowledge graphs, supporting automatic construction and retrieval of context from emails, meeting notes, and other sources.

Design a collaborative management scheme for multiple AI coding agents working in parallel, including task assignment, progress tracking, and skill accumulation.

Input model name and deployment environment to automatically generate a comparative evaluation of inference acceleration technologies, including quantization, distillation, and speculative decoding.

Generate a complete performance benchmarking plan for an AI Agent's sandbox execution environment, including test cases and evaluation criteria for key metrics such as cold start latency, memory isolation, and concurrent execution.

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

Design pre-indexed knowledge graph solutions for large code repositories, allowing AI coding agents to understand project structures before conversations, reducing token consumption and tool calls.

Design a personal AI super assistant system architecture with long-term memory, multi-platform integration, and active perception capabilities

Help you generate high-quality synthetic training data from scratch, supporting custom domains, formats, and quality standards, suitable for fine-tuning and evaluation scenarios.

Generate code change impact scope reports based on semantic analysis rather than text diffs, identifying potential risks and modules requiring regression testing.

Simulate the thinking styles of multiple investment masters to conduct multi-angle analysis of specified stocks and generate comprehensive investment advice.

Design a dialogue system for AI Agents with persistent memory, supporting cross-session memory retrieval, user preference tracking, and context compression.

Design fine-tuning and deployment schemes tailored to specific financial scenarios based on time series foundation models like TimesFM.

Design an Agent memory system based on a temporal knowledge graph, supporting fact version tracking, incremental updates, and hybrid retrieval.

Input your Agent tool list and common error scenarios to automatically generate a complete error handling decision tree, including retry strategies, fallback plans, and user notification templates.

Describe your document types and scale to generate a complete local semantic search system deployment plan, including embedding model selection, vector database configuration, and search API code.

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.

Input exported chat history into the AI to automatically generate social relationship insights, topic trends, sentiment analysis, and annual review reports.

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

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

Compresses lengthy AI coding session histories into structured memory files and accurately restores context in new sessions, significantly reducing token consumption while preserving key decisions and code changes.

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

Designed isolated execution strategies for multi-agent parallel coding scenarios, including task allocation, branch management, conflict detection, and automatic merging schemes, suitable for autonomous coding platforms such as Symphony and OpenHands.

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

Design solutions for remotely managing AI encoding agents from mobile phones, including session synchronization, voice control, notification, and approval workflows

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

Help developers quickly design tool discovery, MCP Server integration, and database connection solutions for AI Agents, generating complete configuration and code templates.

Generate selection recommendations and setup steps for zero-code or low-code AI Agent frameworks based on your needs.

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

Design asynchronous task orchestration schemes for multi-step AI Agents, including retry, timeout, callback, and state machine design.

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

Design a full-stack observability solution for AI Agent applications, covering LLM call tracing, tool execution monitoring, cost analysis, and anomaly detection dashboards.

Design standardized communication protocols and message formats for multi-agent systems, supporting task distribution, state synchronization, error propagation, and result aggregation.

Design an end-to-end financial data prediction and analysis solution based on the latest financial time series foundation models (such as Kronos).

Generate secure sandbox configuration policies for AI agents executing multiple tools, including sandbox isolation and permission control for interfaces such as OpenAPI, MCP, and GraphQL.

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.

Describe your document types and scale to generate a complete local semantic search system deployment plan, including embedding model selection, vector database configuration, and search API code.

Input your agent's tool list and common error scenarios to automatically generate a comprehensive error-handling decision tree, including retry strategies, fallback plans, and user notification templates.

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.

One-click generation of the complete technical architecture for voice AI applications, covering STT, TTS, VAD, dialogue management, and multi-channel integration.

Have the AI act as a quantitative trading analyst, fusing multiple data sources (news, social media, K-lines, on-chain data) to generate structured trading signals, including entry points, stop-loss/take-profit levels, and confidence scores.

Use AI to automatically analyze scattered notes in an Obsidian vault, generating reasonable bi-directional links, tag systems, and MOCs (Maps of Content), transforming the knowledge base from a pile of information into a network of knowledge.

Generate a robust task execution plan for a browser automation AI Agent, including element location strategies, wait conditions, error recovery mechanisms, and human-in-the-loop breakpoint designs.