All prompts

Designing a secure code execution sandbox solution for AI Agents, covering interpreter selection, permission isolation, resource limiting, and snapshot recovery strategies

Based on Kubernetes cloud-native architecture, AI Agent deployment, orchestration, and observability solutions are designed, supporting multi-model and multi-tool integration

Automatically route tasks to the most suitable LLM based on complexity, achieving a smart gateway configuration that reduces costs by 70%.

Rewrite an article to suit different platforms (Xiaohongshu/Twitter/LinkedIn/WeChat Official Account), automatically adjusting tone, length, and format.

Describe your multi-agent system requirements in one sentence, and automatically generate a complete architecture design plan, including agent role definitions, communication protocols, task orchestration, and error handling strategies.

Input the project tech stack and dependency list to generate a complete dependency security audit report, including vulnerability severity, impact scope, and remediation suggestions.

Automatically analyze watchlist stocks using AI to generate a multi-dimensional decision dashboard covering technicals, fundamentals, and sentiment, supporting A-shares, HK stocks, and US stocks.

Design an end-to-end AI Agent workflow that automatically reads ML papers, extracts experimental settings, reproduces the training process, and generates evaluation reports.

Design an end-to-end agentic commerce workflow where an AI Agent autonomously completes product discovery, price comparison, and ordering, suitable for e-commerce automation and intelligent procurement scenarios.

Describe operator requirements in natural language to automatically generate TileLang DSL code, supporting rapid development of common high-performance computing kernels such as GEMM, Attention, and quantization.

Automatically scans the code warehouse for security risks, architectural issues, and technical debt, generating a prioritized repair roadmap and health score

Generates a unified compatibility layer design solution for any AI model API, supporting multi-provider routing and format conversion

Design a comprehensive observability solution for the AI Agent's multi-step task execution chain, including trace, span, log association, and performance metric collection

Describe your business scenario, and AI will help you design a complete multi-agent workflow solution, including role division, tool invocation, and collaboration models

Enter project information, and AI automatically generates a professional GitHub README, including badges, installation guides, usage examples, and contribution guides

Paste your prompt, and AI analyzes it from perspectives such as clarity, structure, constraints, and provides optimized versions and test cases

Design a secure execution scheme for Python code generated by AI Agents, including sandbox isolation, permission control, timeout mechanisms, and output validation, suitable for production scenarios requiring LLM code execution.

Design a workspace architecture supporting collaboration among multiple AI Agents, including task assignment, skill evolution, progress tracking, and conflict resolution mechanisms, suitable for team-level AI coding and operations scenarios.

Input a GitHub repository URL to automatically generate a quick start guide for first-time contributors, including environment setup, code structure, and recommended directions for the first PR.

Input the product name, core features, and target users to generate launch copy for multiple platforms including Twitter/X, Product Hunt, Xiaohongshu, and LinkedIn in one go.

Generates natural language motion descriptions for AI-driven character animation systems, outputting structured motion sequence instructions usable for neural network animation models

Conduct quality reviews of entire LLM-translated books, checking terminology consistency, stylistic consistency, and cultural fit, and provide revision suggestions

Design a fully self-hosted, privacy-first personal knowledge management system integrating local AI for semantic search, automatic tagging, knowledge graphs, and intelligent summarization, with all data remaining local.

A comprehensive guide for AI short film production, from scriptwriting and storyboarding to image generation, voiceover, and music, applicable to video generation tools like Sora, Kling, and others.

Design an architecture to unify batch processing, stream processing, and AI inference workloads into a single high-performance compute engine, replacing traditional distributed deployments of Spark and Flink.

Automated PR lifecycle management from idea to merge, including task assignment, code generation, automatic review, conflict resolution, and merge strategies.

Automatically generate standardized Pull Request descriptions based on code changes, including change summaries, impact analysis, and testing suggestions.

Automatically rewrite a core piece of content into copy adapted for different platforms such as Xiaohongshu, Twitter, LinkedIn, and WeChat Official Accounts.

Quickly layout your research content into a professional academic paper format using Markdown, supporting citations, formulas, figure/table numbering, and automatic reference generation.

Design an AI-based automatic issue triage system for open source project maintainers, including classification rules, priority assessment matrices, and auto-reply templates.

Evaluate the feasibility of running Windows applications on Linux and generate detailed migration plans, including containerization, Wine, native alternatives, and other path comparisons and recommendations. Suitable for teams considering migrating from Windows to Linux.

Converts Git diffs or code changes into clear natural language explanations, helping reviewers quickly understand intent and scope.

Transforms vague user needs into structured Agent task specification documents, including objectives, constraints, steps, and acceptance criteria, ensuring precise execution rather than guessing intent.

Uses LLM multi-agents for automated quantitative factor mining: a complete workflow design prompt covering data cleaning, factor construction, IC analysis, and strategy backtesting, adaptable to platforms like Qlib/RD-Agent.

Before committing code, let AI analyze the modules, dependency chains, and potential risk points affected by the changes to avoid deployment incidents.

Based on users' learning habits, tool preferences, and knowledge areas, a complete personal knowledge management system solution is designed, including tool selection, workflow design, and a progressive roadmap

Designed incremental data processing and persistent memory pipelines for long-cycle AI Agents, supporting efficient state recovery and contextual recall

Cleans chat records from WeChat/QQ into high-quality fine-tuned datasets to train AI digital avatars with personal styles. Automatically filters noise, extracts dialogue patterns, and generates instruction-tuning format data.

Transform vague feature requirements into precise technical specification documents, optimized for direct execution by AI coding assistants.

Design an AI Agent system capable of autonomous learning and skill accumulation, allowing the Agent to automatically build a skill library through task execution.

Analyzes technical debt in codebases, categorizes it by priority, and generates an executable repayment plan suitable for team sprint planning.

Design an AI Agent self-evolution framework based on Gene Expression Programming (GEP), allowing the Agent to autonomously grow its skill tree.

Automatically generate production-grade Docker Compose deployment files based on the open-source project's tech stack and dependencies, including environment variables, persistence, and health checks.

Design anomaly detection rules for AI Agent systems, including monitoring strategies for abnormal token consumption, tool call anomalies, loop detection, and security boundary breaches.

A complete self-evolution loop prompt that enables AI Agents to autonomously discover new skill needs, generate skill code, and validate effects.

Input AI application requirements to generate a deployment solution comparison covering Web/Desktop/Mobile, including a decision matrix for cost, performance, and privacy dimensions.

Generate task assignment rules, file locking strategies, and code merge conflict prevention plans for multi-agent coding teams, enabling AI coding teams to collaborate efficiently like real development teams.

Design initial skill seed files for self-evolving AI agents, including core capability definitions, learning strategies, and evolution path planning.