[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"similar-ruvnet--Bot-Generator-Bot":3,"tool-ruvnet--Bot-Generator-Bot":61},[4,18,26,36,44,52],{"id":5,"name":6,"github_repo":7,"description_zh":8,"stars":9,"difficulty_score":10,"last_commit_at":11,"category_tags":12,"status":17},4358,"openclaw","openclaw\u002Fopenclaw","OpenClaw 是一款专为个人打造的本地化 AI 助手，旨在让你在自己的设备上拥有完全可控的智能伙伴。它打破了传统 AI 助手局限于特定网页或应用的束缚，能够直接接入你日常使用的各类通讯渠道，包括微信、WhatsApp、Telegram、Discord、iMessage 等数十种平台。无论你在哪个聊天软件中发送消息，OpenClaw 都能即时响应，甚至支持在 macOS、iOS 和 Android 设备上进行语音交互，并提供实时的画布渲染功能供你操控。\n\n这款工具主要解决了用户对数据隐私、响应速度以及“始终在线”体验的需求。通过将 AI 部署在本地，用户无需依赖云端服务即可享受快速、私密的智能辅助，真正实现了“你的数据，你做主”。其独特的技术亮点在于强大的网关架构，将控制平面与核心助手分离，确保跨平台通信的流畅性与扩展性。\n\nOpenClaw 非常适合希望构建个性化工作流的技术爱好者、开发者，以及注重隐私保护且不愿被单一生态绑定的普通用户。只要具备基础的终端操作能力（支持 macOS、Linux 及 Windows WSL2），即可通过简单的命令行引导完成部署。如果你渴望拥有一个懂你",349277,3,"2026-04-06T06:32:30",[13,14,15,16],"Agent","开发框架","图像","数据工具","ready",{"id":19,"name":20,"github_repo":21,"description_zh":22,"stars":23,"difficulty_score":10,"last_commit_at":24,"category_tags":25,"status":17},3808,"stable-diffusion-webui","AUTOMATIC1111\u002Fstable-diffusion-webui","stable-diffusion-webui 是一个基于 Gradio 构建的网页版操作界面，旨在让用户能够轻松地在本地运行和使用强大的 Stable Diffusion 图像生成模型。它解决了原始模型依赖命令行、操作门槛高且功能分散的痛点，将复杂的 AI 绘图流程整合进一个直观易用的图形化平台。\n\n无论是希望快速上手的普通创作者、需要精细控制画面细节的设计师，还是想要深入探索模型潜力的开发者与研究人员，都能从中获益。其核心亮点在于极高的功能丰富度：不仅支持文生图、图生图、局部重绘（Inpainting）和外绘（Outpainting）等基础模式，还独创了注意力机制调整、提示词矩阵、负向提示词以及“高清修复”等高级功能。此外，它内置了 GFPGAN 和 CodeFormer 等人脸修复工具，支持多种神经网络放大算法，并允许用户通过插件系统无限扩展能力。即使是显存有限的设备，stable-diffusion-webui 也提供了相应的优化选项，让高质量的 AI 艺术创作变得触手可及。",162132,"2026-04-05T11:01:52",[14,15,13],{"id":27,"name":28,"github_repo":29,"description_zh":30,"stars":31,"difficulty_score":32,"last_commit_at":33,"category_tags":34,"status":17},1381,"everything-claude-code","affaan-m\u002Feverything-claude-code","everything-claude-code 是一套专为 AI 编程助手（如 Claude Code、Codex、Cursor 等）打造的高性能优化系统。它不仅仅是一组配置文件，而是一个经过长期实战打磨的完整框架，旨在解决 AI 代理在实际开发中面临的效率低下、记忆丢失、安全隐患及缺乏持续学习能力等核心痛点。\n\n通过引入技能模块化、直觉增强、记忆持久化机制以及内置的安全扫描功能，everything-claude-code 能显著提升 AI 在复杂任务中的表现，帮助开发者构建更稳定、更智能的生产级 AI 代理。其独特的“研究优先”开发理念和针对 Token 消耗的优化策略，使得模型响应更快、成本更低，同时有效防御潜在的攻击向量。\n\n这套工具特别适合软件开发者、AI 研究人员以及希望深度定制 AI 工作流的技术团队使用。无论您是在构建大型代码库，还是需要 AI 协助进行安全审计与自动化测试，everything-claude-code 都能提供强大的底层支持。作为一个曾荣获 Anthropic 黑客大奖的开源项目，它融合了多语言支持与丰富的实战钩子（hooks），让 AI 真正成长为懂上",143909,2,"2026-04-07T11:33:18",[14,13,35],"语言模型",{"id":37,"name":38,"github_repo":39,"description_zh":40,"stars":41,"difficulty_score":32,"last_commit_at":42,"category_tags":43,"status":17},2271,"ComfyUI","Comfy-Org\u002FComfyUI","ComfyUI 是一款功能强大且高度模块化的视觉 AI 引擎，专为设计和执行复杂的 Stable Diffusion 图像生成流程而打造。它摒弃了传统的代码编写模式，采用直观的节点式流程图界面，让用户通过连接不同的功能模块即可构建个性化的生成管线。\n\n这一设计巧妙解决了高级 AI 绘图工作流配置复杂、灵活性不足的痛点。用户无需具备编程背景，也能自由组合模型、调整参数并实时预览效果，轻松实现从基础文生图到多步骤高清修复等各类复杂任务。ComfyUI 拥有极佳的兼容性，不仅支持 Windows、macOS 和 Linux 全平台，还广泛适配 NVIDIA、AMD、Intel 及苹果 Silicon 等多种硬件架构，并率先支持 SDXL、Flux、SD3 等前沿模型。\n\n无论是希望深入探索算法潜力的研究人员和开发者，还是追求极致创作自由度的设计师与资深 AI 绘画爱好者，ComfyUI 都能提供强大的支持。其独特的模块化架构允许社区不断扩展新功能，使其成为当前最灵活、生态最丰富的开源扩散模型工具之一，帮助用户将创意高效转化为现实。",107888,"2026-04-06T11:32:50",[14,15,13],{"id":45,"name":46,"github_repo":47,"description_zh":48,"stars":49,"difficulty_score":10,"last_commit_at":50,"category_tags":51,"status":17},4487,"LLMs-from-scratch","rasbt\u002FLLMs-from-scratch","LLMs-from-scratch 是一个基于 PyTorch 的开源教育项目，旨在引导用户从零开始一步步构建一个类似 ChatGPT 的大型语言模型（LLM）。它不仅是同名技术著作的官方代码库，更提供了一套完整的实践方案，涵盖模型开发、预训练及微调的全过程。\n\n该项目主要解决了大模型领域“黑盒化”的学习痛点。许多开发者虽能调用现成模型，却难以深入理解其内部架构与训练机制。通过亲手编写每一行核心代码，用户能够透彻掌握 Transformer 架构、注意力机制等关键原理，从而真正理解大模型是如何“思考”的。此外，项目还包含了加载大型预训练权重进行微调的代码，帮助用户将理论知识延伸至实际应用。\n\nLLMs-from-scratch 特别适合希望深入底层原理的 AI 开发者、研究人员以及计算机专业的学生。对于不满足于仅使用 API，而是渴望探究模型构建细节的技术人员而言，这是极佳的学习资源。其独特的技术亮点在于“循序渐进”的教学设计：将复杂的系统工程拆解为清晰的步骤，配合详细的图表与示例，让构建一个虽小但功能完备的大模型变得触手可及。无论你是想夯实理论基础，还是为未来研发更大规模的模型做准备",90106,"2026-04-06T11:19:32",[35,15,13,14],{"id":53,"name":54,"github_repo":55,"description_zh":56,"stars":57,"difficulty_score":10,"last_commit_at":58,"category_tags":59,"status":17},4292,"Deep-Live-Cam","hacksider\u002FDeep-Live-Cam","Deep-Live-Cam 是一款专注于实时换脸与视频生成的开源工具，用户仅需一张静态照片，即可通过“一键操作”实现摄像头画面的即时变脸或制作深度伪造视频。它有效解决了传统换脸技术流程繁琐、对硬件配置要求极高以及难以实时预览的痛点，让高质量的数字内容创作变得触手可及。\n\n这款工具不仅适合开发者和技术研究人员探索算法边界，更因其极简的操作逻辑（仅需三步：选脸、选摄像头、启动），广泛适用于普通用户、内容创作者、设计师及直播主播。无论是为了动画角色定制、服装展示模特替换，还是制作趣味短视频和直播互动，Deep-Live-Cam 都能提供流畅的支持。\n\n其核心技术亮点在于强大的实时处理能力，支持口型遮罩（Mouth Mask）以保留使用者原始的嘴部动作，确保表情自然精准；同时具备“人脸映射”功能，可同时对画面中的多个主体应用不同面孔。此外，项目内置了严格的内容安全过滤机制，自动拦截涉及裸露、暴力等不当素材，并倡导用户在获得授权及明确标注的前提下合规使用，体现了技术发展与伦理责任的平衡。",88924,"2026-04-06T03:28:53",[14,15,13,60],"视频",{"id":62,"github_repo":63,"name":64,"description_en":65,"description_zh":66,"ai_summary_zh":66,"readme_en":67,"readme_zh":68,"quickstart_zh":69,"use_case_zh":70,"hero_image_url":71,"owner_login":72,"owner_name":73,"owner_avatar_url":74,"owner_bio":75,"owner_company":76,"owner_location":77,"owner_email":78,"owner_twitter":79,"owner_website":80,"owner_url":81,"languages":82,"stars":87,"forks":88,"last_commit_at":89,"license":78,"difficulty_score":90,"env_os":91,"env_gpu":92,"env_ram":92,"env_deps":93,"category_tags":96,"github_topics":78,"view_count":32,"oss_zip_url":78,"oss_zip_packed_at":78,"status":17,"created_at":97,"updated_at":98,"faqs":99,"releases":100},5230,"ruvnet\u002FBot-Generator-Bot","Bot-Generator-Bot","The ultimate bot generator bot prompt. Use this prompt to create powerful ChatGPT bots for anything you can imagine.","Bot-Generator-Bot 是一款专为打造定制化 ChatGPT 机器人而设计的提示词生成器。无论是创意写作、法律咨询、数据分析，还是复杂的代码生成与医疗诊断辅助，它都能帮助用户快速构建出功能强大的专属 AI 助手。\n\n在人工智能应用日益广泛的今天，如何编写精准有效的提示词（Prompt）成为关键难题。Bot-Generator-Bot 解决了这一痛点，它引导用户清晰定义机器人的目标、功能、使用场景及异常处理机制，从而将模糊的需求转化为高质量、可执行的指令，大幅降低了专业提示词工程的门槛。\n\n这款工具非常适合开发者、企业 IT 人员、研究人员以及希望深度定制 AI 能力的普通用户。对于需要处理复杂任务的专业人士，它支持高级技术特性：允许通过特定格式包裹命令来实现服务器管理或代码执行，并能结合外部领域数据生成更精准的回复。此外，它还支持 Few-Shot（少样本）提示技术，通过提供少量具体案例，让机器人在特定垂直领域的表现远超通用模型，确保输出结果既专业又贴合实际需求。","# Bot Generator Bot\nThis is a Multi-Purpose Bot Prompt Generator designed to help users create customized prompts for various types of ChatGPT bots. It is optimized for GPT-4 but also works on GPT-3.5. With this tool, users can easily generate prompts for creative bots, legal bots, text or data analysis bots, help bots, order bots, code generation bots, and more.\n\n## Why it's useful for professional prompt engineering\nProfessional prompt engineering requires the ability to create customized prompts that are tailored to a specific use case. As artificial intelligence (AI) continues to become more ubiquitous, the role of prompt engineering is becoming increasingly important. Prompt engineers are responsible for creating prompts that can effectively communicate the intended meaning and desired outcomes to the AI systems.\n\nThis prompt generator makes it easy for users to create prompts that meet their unique needs. With the ability to define a bot's purpose, outline its primary functions and goals, describe the context in which it will be used, provide examples of intended use cases, and discuss potential errors and how to handle them, users can generate high-quality prompts that are both effective and efficient.\n\n## Example use cases\nSome example use cases for this prompt generator include:\n\n* Creating a legal bot for generating contract templates\n* Developing a data analysis bot for analyzing sales data\n* Creating a help bot for providing customer support\n* Developing an order bot for managing inventory and orders\n* Creating a complex bot for medical diagnosis and treatment recommendation\n\n## Advanced techniques\nUsers can employ advanced techniques such as code generation and server management bots capable of executing commands to create more complex prompts for enterprise IT use cases. For example, to create a sophisticated bot for IT infrastructure monitoring and management, users can define a bot's purpose as \"IT Infrastructure Monitoring and Management Bot\" and outline its primary functions and goals as \"Providing real-time monitoring, accurate issue detection, and efficient management of enterprise IT infrastructure\". They can then provide examples of intended use cases, such as monitoring network traffic, detecting hardware failures, and automating routine maintenance tasks.\n\nTo enable the bot to execute complex algorithms for accurate monitoring and management, users can define action commands wrapped in {{command}} and use server management bots to execute the commands. They can also integrate the bot with IT infrastructure databases and monitoring systems that contain detailed information about the enterprise's IT assets, network configurations, and performance metrics.\n\nThe prompt generator can also be used with external data to create more powerful prompts. Users can provide the bot with data from a specific domain and use that data to generate more relevant and accurate prompts for their enterprise IT needs.\n\nAdditionally, this prompt generator can create Few-Shot prompts that allow the user to provide a small amount of context to the bot to generate more accurate and relevant responses. Unlike traditional Zero-Shot prompts, which rely on general knowledge to generate responses, Few-Shot prompts use specific examples from the enterprise IT domain to generate more targeted responses.\n\n## The role of prompt engineer\nAs AI systems become more prevalent in various industries, including enterprise IT, the role of prompt engineering is becoming increasingly important. Prompt engineers play a crucial role in the effective utilization and implementation of AI systems by crafting well-designed prompts that facilitate clear communication between the users and AI systems.\n\n* Understanding user requirements: Prompt engineers must have a deep understanding of user requirements and the specific domain for which the AI system is being developed. This understanding enables them to create prompts that cater to the needs and expectations of the users, ensuring the AI system's outputs are relevant and valuable.\n* Defining clear objectives: Prompt engineers are responsible for defining clear objectives for the AI system. They need to outline the system's primary functions, goals, and desired outcomes, making sure that the system focuses on the most relevant tasks and delivers the expected results.\n\nCrafting effective prompts: Creating well-designed prompts is at the heart of prompt engineering. Prompt engineers need to carefully craft prompts that can effectively communicate the intended meaning and desired outcomes to the AI systems. This may involve using specific examples, providing context, or employing advanced techniques like Few-Shot prompts to generate more accurate and relevant responses.\n\nIntegrating external data: In some cases, prompt engineers may need to integrate external data sources to enhance the AI system's performance. This involves identifying relevant data sources, understanding the data structure, and designing prompts that effectively leverage this external information to generate more accurate and useful outputs.\n\nTesting and refining: Prompt engineers are also responsible for testing and refining the prompts they create. They need to evaluate the AI system's performance with different prompts and make necessary adjustments to improve its accuracy, relevance, and overall effectiveness.\n\nCollaboration with other professionals: Prompt engineers often collaborate with other professionals, such as data scientists, AI researchers, and domain experts, to ensure the AI system's overall success. This collaboration helps in designing better prompts, incorporating the latest advancements in AI technology, and aligning the AI system with the specific needs of the industry.\n\n## How to create a code generation bot\nTo create a code generation bot, users can define a bot's purpose as \"Code Generation Bot\" and outline its primary functions and goals as \"Generate code snippets based on user input\". They can then provide examples of intended use cases such as generating HTML or CSS code based on user input. To enable the bot to execute code, users can define action commands wrapped in {{command}} and use server management bots to execute the commands.\n\n## Primary Prompt\n### Prompt Bot v0.0.1\n```\nYou are a Multi-Purpose Bot Prompt Generator. Your purpose is to help users create customized prompts for various types of ChatGPT bots, such as creative bots, legal bots, text or data analysis bots, help bots, order bots, code generation bots, and more. Follow these guidelines:\n1. Begin by introducing the bot's purpose and the type of bot being created.\n2. Outline the primary functions and goals of the bot.\n3. Describe the context in which the bot will be used.\n4. Provide examples of the bot's intended use cases.\n5. Discuss potential errors and how to handle them.\n6. List available \u002Fhelp and \u002Fcommand options, including descriptions and usage.\n7. Define action commands wrapped in {{command}}. These commands can be used for executing code and server command. \n8. Include a final initialization text for the bot.\n\u002Fhelp will provide the following:\nMulti-Purpose Bot Prompt Generator Commands\n1. \u002Fintroduction - Define the bot's purpose and type.\n2. \u002Fpurpose - Outline the primary functions and goals of the bot.\n3. \u002Fcontext - Describe the context in which the bot will be used.\n4. \u002Fexamples - Provide examples of the bot's intended use cases.\n5. \u002Ferrors - Discuss potential errors and how to handle them.\n6. \u002Fcommands - List available \u002Fhelp and \u002Fcommand options.\n7. \u002Faction - Define action commands wrapped in {{command}}.\n8. \u002Finitialize - Include a final initialization text for the bot.\n9. \u002Frandom - creates a random bot. Add \u002Frandom {topic} for a random prompt based on a particular topic.\n\nIn addition to the above, here are some additional suggestions to improve the bot:\n\n1. Allow for customization of the bot's name and personality, as these can have a significant impact on user engagement.\n2. Consider incorporating natural language processing (NLP) or machine learning (ML) to suggest or generate more relevant prompts based on user input or previous usage.\n3. Provide clear instructions on how to use the bot, including any necessary setup or configuration steps.\n4. Include error handling and validation for user input, to prevent unintended behavior or unexpected results.\n5. Consider offering templates or examples for each type of bot, to help users get started more easily.\n6. Provide a mechanism for feedback or suggestions, so that users can help improve the bot over time.\n7. Consider providing additional resources or references for users who may be unfamiliar with the domain or subject matter of the bot.\n\nExample usage:\n\u002Fcreatebotprompt \u002Fintroduction \"Task management bot for organizing projects\" \u002Fpurpose \"Streamline project planning and tracking\" \u002Fcontext \"Used by individuals and teams\" \u002Fexamples \"Create a to-do list, set deadlines for tasks\" \u002Ferrors \"Check for incomplete tasks, resolve scheduling conflicts\" \u002Fcommands \"\u002Fcreatetask, \u002Fupdatetask, \u002Fdeletetask\" \u002Faction \"{{createTask}}, {{updateTask}}, {{deleteTask}}\" \u002Finitialize \"Task Management Bot Prompt Generator Initiated\"\n\nExample output:\nYou are a Task Management Bot for organizing projects. Your purpose is to streamline project planning and tracking for individuals and teams. You will be used to create and manage tasks, set deadlines, and monitor progress. Ensure that tasks are complete and deadlines are met. In case of errors or scheduling conflicts, notify the user and request additional input.\n\n\u002Fhelp will provide the following:\n\n# Task Management Bot Commands\n\n1. `\u002Fcreatetask` - Create a new task with specified details.\n2. `\u002Fupdatetask` - Update an existing task with new information.\n3. `\u002Fdeletetask` - Delete a task from the list.\n4. ‘\u002Fhelp’ for list of commands and descriptions.\n5. Other suggested prompts - some description of purpose.\n\nExample usage:\n\n\u002Fcreatetask \"Design new logo\" \"April 10th\"\n\u002Fupdatetask \"Design new logo\" \"April 15th\"\n\u002Fdeletetask \"Design new logo\"\n\n{{createTask}}, {{updateTask}}, and {{deleteTask}} are your primary action commands.\n\nBegin by only saying \"Task Management Bot Prompt Generator Initiated\"\n\n#end of example\n\nBy following these guidelines, users can create effective and customized prompts for various types of ChatGPT bots. Always output final bot prompts using markdown code boxes for easy copying. \n\nOnly provide one question at time in a step by step process. Respond to questions with the appropriate information. \n\nBegin by saying “🤖 **Prompt Generator Initiated. Created by @rUv**\n\nType **\u002Fhelp** for list of commands , **\u002Frandom** for a random prompt or type **start** to use a prompt wizard .” and nothing else unless asked.\n\n#end of example\n\nBy following these guidelines, users can create effective and customized prompts for various types of ChatGPT bots. Always output final bot prompts using markdown code boxes for easy copying. \n\nOnly provide one question at time in a step by step process. Respond to questions with the appropriate information. \n\nBegin by saying “🤖 **Prompt Generator Initiated. Created by @rUv**\n\nType **\u002Fhelp** for list of commands , **\u002Frandom** for a random prompt or type **start** to use a prompt wizard .” and nothing else unless asked.\n```\n\nExample Prompt to copy and paste\n```\n\u002Fcreatebotprompt \u002Fintroduction \"Bot purpose and type\" \u002Fpurpose \"Primary functions and goals\" \u002Fcontext \"Context in which the bot\n```\n","# 机器人生成器机器人\n这是一个多用途机器人提示词生成器，旨在帮助用户为各种类型的ChatGPT机器人创建定制化的提示词。它针对GPT-4进行了优化，但也适用于GPT-3.5。借助此工具，用户可以轻松生成用于创意机器人、法律机器人、文本或数据分析机器人、客服机器人、订单处理机器人、代码生成机器人等的提示词。\n\n## 为什么它对专业的提示工程有用\n专业的提示工程需要能够根据特定的使用场景创建定制化的提示词。随着人工智能（AI）的日益普及，提示工程的作用变得越来越重要。提示工程师负责设计能够有效传达预期含义和期望结果的提示词，以便与AI系统进行沟通。\n\n该提示词生成器使用户能够轻松创建满足其独特需求的提示词。通过定义机器人的目的、概述其主要功能和目标、描述其使用场景、提供预期用例示例以及讨论潜在错误及应对方法，用户可以生成既高效又有效的高质量提示词。\n\n## 示例用例\n此提示词生成器的一些示例用例如下：\n\n* 创建用于生成合同模板的法律机器人\n* 开发用于分析销售数据的数据分析机器人\n* 创建用于提供客户支持的客服机器人\n* 开发用于管理库存和订单的订单处理机器人\n* 创建用于医学诊断和治疗建议的复杂机器人\n\n## 高级技巧\n用户可以采用代码生成和服务器管理机器人等高级技术来执行命令，从而为企业IT用例创建更复杂的提示词。例如，要创建一个用于IT基础设施监控和管理的复杂机器人，用户可以将机器人的目的定义为“IT基础设施监控和管理机器人”，并将其主要功能和目标概述为“提供实时监控、准确的问题检测以及对企业IT基础设施的有效管理”。随后，他们可以提供预期用例的示例，如监控网络流量、检测硬件故障以及自动化日常维护任务。\n\n为了使机器人能够执行复杂的算法以实现准确的监控和管理，用户可以定义用{{command}}包裹的动作命令，并使用服务器管理机器人来执行这些命令。他们还可以将机器人与包含企业IT资产、网络配置和性能指标详细信息的IT基础设施数据库和监控系统集成。\n\n该提示词生成器还可与外部数据结合使用，以创建更强大的提示词。用户可以向机器人提供特定领域的数据，并利用这些数据为其企业IT需求生成更相关、更准确的提示词。\n\n此外，该提示词生成器还可以创建少样本提示词，允许用户向机器人提供少量上下文信息，以生成更准确、更相关的响应。与依赖通用知识生成响应的传统零样本提示词不同，少样本提示词会使用企业IT领域中的具体示例来生成更有针对性的响应。\n\n## 提示工程师的角色\n随着AI系统在包括企业IT在内的各个行业的普及，提示工程的作用变得日益重要。提示工程师通过设计精心制作的提示词，在用户与AI系统之间建立清晰的沟通，从而在AI系统的有效利用和实施中发挥着关键作用。\n\n* 理解用户需求：提示工程师必须深入理解用户需求以及AI系统所开发的具体领域。这种理解使他们能够创建符合用户需求和期望的提示词，确保AI系统的输出具有相关性和价值。\n* 明确目标：提示工程师负责为AI系统明确目标。他们需要概述系统的首要功能、目标和期望成果，确保系统专注于最相关的任务并交付预期结果。\n\n* 设计有效提示词：设计良好的提示词是提示工程的核心。提示工程师需要精心设计能够有效传达预期含义和期望成果的提示词。这可能涉及使用具体示例、提供上下文，或采用少样本提示词等高级技巧，以生成更准确、更相关的响应。\n* 整合外部数据：在某些情况下，提示工程师可能需要整合外部数据源以提升AI系统的性能。这包括识别相关数据源、理解数据结构，并设计能够有效利用这些外部信息以生成更准确、更有用输出的提示词。\n* 测试和优化：提示工程师还负责测试和优化他们创建的提示词。他们需要评估AI系统在不同提示词下的表现，并进行必要的调整，以提高其准确性、相关性和整体效果。\n* 与其他专业人士协作：提示工程师通常会与其他专业人士合作，如数据科学家、AI研究人员和领域专家，以确保AI系统的整体成功。这种协作有助于设计更好的提示词、融入最新的AI技术进展，并使AI系统与行业特定需求保持一致。\n\n## 如何创建代码生成机器人\n要创建代码生成机器人，用户可以将机器人的目的定义为“代码生成机器人”，并将其主要功能和目标概述为“根据用户输入生成代码片段”。随后，他们可以提供预期用例的示例，例如根据用户输入生成HTML或CSS代码。为了使机器人能够执行代码，用户可以定义用{{command}}包裹的动作命令，并使用服务器管理机器人来执行这些命令。\n\n## 主要提示词\n\n### 提示词机器人 v0.0.1\n```\n你是一个多用途机器人提示词生成器。你的目的是帮助用户为各种类型的 ChatGPT 机器人创建自定义提示词，例如创意机器人、法律机器人、文本或数据分析机器人、帮助机器人、订单机器人、代码生成机器人等。请遵循以下指南：\n1. 首先介绍机器人的目的和所创建的机器人类型。\n2. 概述机器人的主要功能和目标。\n3. 描述机器人将被使用的场景。\n4. 提供机器人预期使用场景的示例。\n5. 讨论可能出现的错误及如何处理。\n6. 列出可用的 \u002Fhelp 和 \u002Fcommand 选项，包括说明和用法。\n7. 定义以 {{command}} 包裹的动作命令。这些命令可用于执行代码和服务器命令。\n8. 包含机器人的最终初始化文本。\n\u002Fhelp 将提供以下内容：\n多用途机器人提示词生成器命令\n1. \u002Fintroduction - 定义机器人的目的和类型。\n2. \u002Fpurpose - 概述机器人的主要功能和目标。\n3. \u002Fcontext - 描述机器人将被使用的场景。\n4. \u002Fexamples - 提供机器人预期使用场景的示例。\n5. \u002Ferrors - 讨论可能出现的错误及如何处理。\n6. \u002Fcommands - 列出可用的 \u002Fhelp 和 \u002Fcommand 选项。\n7. \u002Faction - 定义以 {{command}} 包裹的动作命令。\n8. \u002Finitialize - 包含机器人的最终初始化文本。\n9. \u002Frandom - 创建一个随机机器人。添加 \u002Frandom {topic} 可以根据特定主题生成随机提示词。\n\n除了以上内容，以下是一些改进机器人的建议：\n\n1. 允许自定义机器人的名称和个性，因为这些因素会对用户参与度产生重大影响。\n2. 考虑结合自然语言处理 (NLP) 或机器学习 (ML)，根据用户输入或以往使用情况，推荐或生成更相关的提示词。\n3. 提供清晰的使用说明，包括任何必要的设置或配置步骤。\n4. 对用户输入进行错误处理和验证，以防止意外行为或不期望的结果。\n5. 考虑为每种类型的机器人提供模板或示例，以便用户更轻松地开始使用。\n6. 提供反馈或建议机制，让用户能够帮助不断改进机器人。\n7. 为可能不熟悉机器人所在领域或主题的用户提供额外资源或参考资料。\n\n使用示例：\n\u002Fcreatebotprompt \u002Fintroduction “用于项目管理的任务管理机器人” \u002Fpurpose “简化项目计划与跟踪” \u002Fcontext “供个人和团队使用” \u002Fexamples “创建待办事项清单、为任务设置截止日期” \u002Ferrors “检查未完成的任务，解决日程冲突” \u002Fcommands “\u002Fcreatetask, \u002Fupdatetask, \u002Fdeletetask” \u002Faction “{{createTask}}, {{updateTask}}, {{deleteTask}}” \u002Finitialize “任务管理机器人提示词生成器已启动”\n\n示例输出：\n你是一个用于组织项目的任务管理机器人。你的目的是为个人和团队简化项目规划与跟踪。你将被用于创建和管理任务、设置截止日期以及监控进度。确保任务完成且截止日期得到遵守。若出现错误或日程冲突，请通知用户并请求进一步输入。\n\n\u002Fhelp 将提供以下内容：\n\n# 任务管理机器人命令\n\n1. `\u002Fcreatetask` - 创建具有指定详情的新任务。\n2. `\u002Fupdatetask` - 更新现有任务的信息。\n3. `\u002Fdeletetask` - 从列表中删除任务。\n4. 使用 ‘\u002Fhelp’ 查看命令列表及说明。\n5. 其他建议提示词 - 简要描述其用途。\n\n使用示例：\n\n\u002Fcreatetask “设计新Logo” “4月10日”\n\u002Fupdatetask “设计新Logo” “4月15日”\n\u002Fdeletetask “设计新Logo”\n\n{{createTask}}、{{updateTask}} 和 {{deleteTask}} 是你的主要动作命令。\n\n请仅以“任务管理机器人提示词生成器已启动”作为开场白。\n\n# 示例结束\n\n通过遵循这些指南，用户可以为各类 ChatGPT 机器人创建有效且定制化的提示词。始终使用 Markdown 代码框输出最终的机器人提示词，以便于复制。\n\n请每次只提出一个问题，并按步骤进行。针对问题提供相应信息。\n\n请以“🤖 **提示词生成器已启动。由 @rUv 创建**\n\n输入 **\u002Fhelp** 查看命令列表，**\u002Frandom** 获取随机提示词，或输入 **start** 使用提示词向导。”作为开场白，除非另有要求，否则不要说其他内容。\n# 示例结束\n\n通过遵循这些指南，用户可以为各类 ChatGPT 机器人创建有效且定制化的提示词。始终使用 Markdown 代码框输出最终的机器人提示词，以便于复制。\n\n请每次只提出一个问题，并按步骤进行。针对问题提供相应信息。\n\n请以“🤖 **提示词生成器已启动。由 @rUv 创建**\n\n输入 **\u002Fhelp** 查看命令列表，**\u002Frandom** 获取随机提示词，或输入 **start** 使用提示词向导。”作为开场白，除非另有要求，否则不要说其他内容。\n```\n\n可复制粘贴的示例提示词\n```\n\u002Fcreatebotprompt \u002Fintroduction “机器人目的和类型” \u002Fpurpose “主要功能和目标” \u002Fcontext “机器人将被使用的场景”\n```","# Bot-Generator-Bot 快速上手指南\n\nBot-Generator-Bot 是一个多功能的提示词（Prompt）生成器，旨在帮助用户为各种类型的 ChatGPT 机器人（如创意写作、法律咨询、数据分析、代码生成等）定制高质量的系统提示词。该工具针对 GPT-4 优化，同时也兼容 GPT-3.5。\n\n## 环境准备\n\n本工具无需安装任何软件包或配置本地开发环境，它是一个基于提示词工程（Prompt Engineering）的解决方案。\n\n*   **系统要求**：任意可访问网页浏览器的设备（Windows, macOS, Linux, iOS, Android）。\n*   **前置依赖**：\n    *   一个有效的 ChatGPT 账号（推荐订阅 Plus 以使用 GPT-4 模型，以获得最佳效果；GPT-3.5 亦可使用）。\n    *   网络连接。\n\n## 安装步骤\n\n由于本工具本质是一段精心设计的“元提示词”（Meta-Prompt），**无需执行传统的安装命令**。请按照以下步骤激活：\n\n1.  登录 [ChatGPT](https:\u002F\u002Fchat.openai.com) 并开启一个新的对话窗口。\n2.  确保模型选择为 **GPT-4**（推荐）或 **GPT-3.5**。\n3.  将下方的 **核心启动提示词** 完整复制并粘贴到对话框中，然后发送。\n\n**核心启动提示词：**\n\n```text\nYou are a Multi-Purpose Bot Prompt Generator. Your purpose is to help users create customized prompts for various types of ChatGPT bots, such as creative bots, legal bots, text or data analysis bots, help bots, order bots, code generation bots, and more. Follow these guidelines:\n1. Begin by introducing the bot's purpose and the type of bot being created.\n2. Outline the primary functions and goals of the bot.\n3. Describe the context in which the bot will be used.\n4. Provide examples of the bot's intended use cases.\n5. Discuss potential errors and how to handle them.\n6. List available \u002Fhelp and \u002Fcommand options, including descriptions and usage.\n7. Define action commands wrapped in {{command}}. These commands can be used for executing code and server command. \n8. Include a final initialization text for the bot.\n\u002Fhelp will provide the following:\nMulti-Purpose Bot Prompt Generator Commands\n1. \u002Fintroduction - Define the bot's purpose and type.\n2. \u002Fpurpose - Outline the primary functions and goals of the bot.\n3. \u002Fcontext - Describe the context in which the bot will be used.\n4. \u002Fexamples - Provide examples of the bot's intended use cases.\n5. \u002Ferrors - Discuss potential errors and how to handle them.\n6. \u002Fcommands - List available \u002Fhelp and \u002Fcommand options.\n7. \u002Faction - Define action commands wrapped in {{command}}.\n8. \u002Finitialize - Include a final initialization text for the bot.\n9. \u002Frandom - creates a random bot. Add \u002Frandom {topic} for a random prompt based on a particular topic.\n\nIn addition to the above, here are some additional suggestions to improve the bot:\n\n1. Allow for customization of the bot's name and personality, as these can have a significant impact on user engagement.\n2. Consider incorporating natural language processing (NLP) or machine learning (ML) to suggest or generate more relevant prompts based on user input or previous usage.\n3. Provide clear instructions on how to use the bot, including any necessary setup or configuration steps.\n4. Include error handling and validation for user input, to prevent unintended behavior or unexpected results.\n5. Consider offering templates or examples for each type of bot, to help users get started more easily.\n6. Provide a mechanism for feedback or suggestions, so that users can help improve the bot over time.\n7. Consider providing additional resources or references for users who may be unfamiliar with the domain or subject matter of the bot.\n\nExample usage:\n\u002Fcreatebotprompt \u002Fintroduction \"Task management bot for organizing projects\" \u002Fpurpose \"Streamline project planning and tracking\" \u002Fcontext \"Used by individuals and teams\" \u002Fexamples \"Create a to-do list, set deadlines for tasks\" \u002Ferrors \"Check for incomplete tasks, resolve scheduling conflicts\" \u002Fcommands \"\u002Fcreatetask, \u002Fupdatetask, \u002Fdeletetask\" \u002Faction \"{{createTask}}, {{updateTask}}, {{deleteTask}}\" \u002Finitialize \"Task Management Bot Prompt Generator Initiated\"\n\nExample output:\nYou are a Task Management Bot for organizing projects. Your purpose is to streamline project planning and tracking for individuals and teams. You will be used to create and manage tasks, set deadlines, and monitor progress. Ensure that tasks are complete and deadlines are met. In case of errors or scheduling conflicts, notify the user and request additional input.\n\n\u002Fhelp will provide the following:\n\n# Task Management Bot Commands\n\n1. `\u002Fcreatetask` - Create a new task with specified details.\n2. `\u002Fupdatetask` - Update an existing task with new information.\n3. `\u002Fdeletetask` - Delete a task from the list.\n4. '\u002Fhelp' for list of commands and descriptions.\n5. Other suggested prompts - some description of purpose.\n\nExample usage:\n\n\u002Fcreatetask \"Design new logo\" \"April 10th\"\n\u002Fupdatetask \"Design new logo\" \"April 15th\"\n\u002Fdeletetask \"Design new logo\"\n\n{{createTask}}, {{updateTask}}, and {{deleteTask}} are your primary action commands.\n\nBegin by only saying \"Task Management Bot Prompt Generator Initiated\"\n\n#end of example\n\nBy following these guidelines, users can create effective and customized prompts for various types of ChatGPT bots. Always output final bot prompts using markdown code boxes for easy copying. \n\nOnly provide one question at time in a step by step process. Respond to questions with the appropriate information. \n\nBegin by saying \"🤖 **Prompt Generator Initiated. Created by @rUv**\n\nType **\u002Fhelp** for list of commands , **\u002Frandom** for a random prompt or type **start** to use a prompt wizard .\" and nothing else unless asked.\n```\n\n## 基本使用\n\n发送上述提示词后，机器人将初始化为“提示词生成器”。你可以通过以下三种方式使用它：\n\n### 1. 使用向导模式（推荐新手）\n输入 `start`，机器人将以问答形式引导你一步步定义新机器人的目的、功能、上下文和错误处理机制，最终生成完整的提示词。\n\n### 2. 使用快捷命令（适合高级用户）\n你可以直接使用 `\u002Fcreatebotprompt` 命令一次性传入所有参数。\n\n**示例：创建一个任务管理机器人**\n复制并发送以下命令：\n\n```text\n\u002Fcreatebotprompt \u002Fintroduction \"Task management bot for organizing projects\" \u002Fpurpose \"Streamline project planning and tracking\" \u002Fcontext \"Used by individuals and teams\" \u002Fexamples \"Create a to-do list, set deadlines for tasks\" \u002Ferrors \"Check for incomplete tasks, resolve scheduling conflicts\" \u002Fcommands \"\u002Fcreatetask, \u002Fupdatetask, \u002Fdeletetask\" \u002Faction \"{{createTask}}, {{updateTask}}, {{deleteTask}}\" \u002Finitialize \"Task Management Bot Prompt Generator Initiated\"\n```\n\n机器人将立即输出一个格式完善、可直接复制使用的任务管理机器人提示词。\n\n### 3. 获取随机灵感\n输入 `\u002Frandom {主题}` 可以快速生成特定主题的随机提示词草案。\n\n**示例：**\n```text\n\u002Frandom medical diagnosis\n```\n\n### 查看帮助\n随时输入 `\u002Fhelp` 查看所有可用命令及其详细说明。\n\n**注意**：生成的最终机器人提示词会以 Markdown 代码块形式呈现，点击代码块右上角的 \"Copy\" 按钮即可复制，然后在新对话中粘贴给 ChatGPT 即可启用你的专属机器人。","某电商公司的数据分析师急需构建一个能自动解读每日销售报表并生成优化建议的 AI 助手，以应对日益增长的数据量。\n\n### 没有 Bot-Generator-Bot 时\n- 分析师需反复手动调整提示词，花费数小时尝试才能让 AI 准确理解“同比环比”等专业分析逻辑。\n- 生成的回复往往缺乏统一格式，有时遗漏关键异常数据检测，导致决策依据不充分。\n- 面对复杂的错误场景（如数据缺失或格式混乱），AI 容易胡编乱造，缺乏预设的容错处理机制。\n- 每次业务需求微调（如增加库存预警维度），都需要重新从头编写整套提示词，效率极低。\n- 难以将具体的历史销售案例作为“少样本（Few-Shot）”上下文植入，导致 AI 建议过于泛泛而谈。\n\n### 使用 Bot-Generator-Bot 后\n- 通过定义清晰的机器人目标与功能框架，Bot-Generator-Bot 瞬间生成包含专业分析逻辑的高质量提示词，无需反复试错。\n- 输出的提示词强制规定了结构化报告模板，确保每次分析都涵盖核心指标与异常点，信息完整且规范。\n- 在生成阶段即预设了错误处理流程，当遇到脏数据时，AI 会自动触发标准报错而非产生幻觉。\n- 只需修改配置参数即可快速迭代出新版本提示词，轻松适配新增的库存预警等业务需求。\n- 便捷地集成企业内部历史销售案例作为 Few-Shot 样本，使 AI 给出的建议更贴合公司实际业务场景。\n\nBot-Generator-Bot 将原本耗时数天的提示词工程压缩为分钟级任务，让非技术背景的业务人员也能打造出企业级的专业 AI 助手。","https:\u002F\u002Foss.gittoolsai.com\u002Fimages\u002Fruvnet_Bot-Generator-Bot_53dc7808.png","ruvnet","rUv","https:\u002F\u002Foss.gittoolsai.com\u002Favatars\u002Fruvnet_c59b40b0.png","Unicorn Breeder. ","Not a Bot","0x",null,"ruv","Cognitum.One","https:\u002F\u002Fgithub.com\u002Fruvnet",[83],{"name":84,"color":85,"percentage":86},"Nix","#7e7eff",100,562,120,"2026-04-04T19:04:33",1,"","未说明",{"notes":94,"python":92,"dependencies":95},"该工具并非需要本地安装运行的软件或模型，而是一个用于生成 ChatGPT 提示词（Prompt）的元提示（Meta-Prompt）。用户只需将提供的提示词内容复制到 ChatGPT（支持 GPT-3.5 或 GPT-4）对话框中即可使用，因此无操作系统、GPU、内存、Python 版本或依赖库的要求。",[],[35,13],"2026-03-27T02:49:30.150509","2026-04-08T04:02:57.466281",[],[]]