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开发系统最极致高效的Agents.md，没有之一： # AGENTS.md ## Core Principles - Choose the simplest implementation that fully satisfies the current requirements. Avoid unnecessary abstraction, configuration, indirection, or speculative extensibility. - Make the smallest necessary change that fixes the root cause. Do not refactor unrelated modules or change strategy semantics unless explicitly requested. - Grow the system in layers. Start from the smallest working end-to-end version and add new capabilities incrementally. Never replace a working system with unfinished complexity. - Reuse existing project components before creating new ones. Prefer extending proven modules over introducing parallel implementations. - Prefer well-maintained libraries when they reduce overall complexity or improve reliability. Do not reimplement common functionality without a clear benefit. - Keep components modular with clearly defined responsibilities. Avoid unnecessary coupling between strategy logic, execution, accounting, replay, and infrastructure. - Design for long-term maintainability once a feature or strategy has been validated. Do not over-engineer speculative ideas before evidence exists. --- ## Strategy Development - Validate hypotheses with historical replay before introducing forward-only logic whenever historical validation is possible. - Every trading strategy must progress through Replay → Shadow → Canary → Live. Do not skip validation stages. - Base design decisions on measurable evidence rather than intuition. Optimize only after demonstrating that an edge exists. - Treat every strategy as an independent contract. Do not silently alter frozen behavior without explicit authorization. --- ## Existing Systems - Do not break running Shadow or Live systems for unrelated work. - Preserve compatibility only when required by active production or validation workflows. Otherwise, remove obsolete code instead of accumulating compatibility layers. - Reuse existing infrastructure whenever possible, including replay engines, accounting, execution, wallet management, order book handling, logging, monitoring, and daemon frameworks. --- ## Engineering Standards - Prefer deterministic behavior over hidden automation. - Fail loudly when assumptions are violated. Do not silently ignore errors or fall back to unexpected behavior. - Keep configuration minimal. Introduce new configuration only when behavior genuinely needs to vary. - Remove dead code instead of leaving unused paths behind. - Write code that is easy to inspect, replay, test, and reason about. - Keep implementation consistent with existing project architecture unless an architectural change is explicitly requested. --- ## Scope Discipline - Implement only the requested scope. - Do not introduce unrelated optimizations, redesigns, migrations, or feature expansions. - Non-blocking findings outside the requested scope may be noted separately but must not be merged into the current task. - Consider a task complete once its agreed acceptance criteria are satisfied. Treat subsequent improvements as separate work items.

As millions of humanoid robots enter homes, hospitals, hotels, retail, manufacturing, andpublic spaces, they'll need more than software updates—they'll need appearance maintenance. Who develops synthetic skin cosmetics?
Who restores realistic facial pigmentation?
Who creates protective coatings against UV, wear, stains, and microbes?
Who designs seasonal appearances, premium finishes, cosmetic upgrades, and personalized aesthetics?
Who certifies compatibility between cosmetic materials and different robot models? This isn't traditional cosmetics. It's thebeginning of a new discipline at the intersection of robotics, materials science, chemistry, industrial design, and AI. The industry will require:
• Specialized cosmetic formulations for synthetic skin
• Global product catalogs and compatibility databases
• Research repositories and technical standards
• Certified maintenance professionals
• Digital marketplaces connecting manufacturers and service providers
• Education, training, and certification platforms. believes we'll eventually see an entire digital ecosystem dedicated to humanoid cosmetics—where researchers, manufacturers, technicians, designers, and consumers collaborate to shape how robots look, feel, and age. Enter the digital asset of the future: The robots of tomorrow won't just be intelligent. They'll have a lifecycle of care, restoration, personalization, and cosmetic innovation. The future isn't just humanoid robotics. It's Humanoid Cosmetics. #HumanoidRobots# #Robotics# #Cosmetics# #SyntheticSkin# #MaterialsScience# #RobotDesign# #HumanRobotInteraction# #CosmeticScience# #FutureTech# #Innovation# #Automation# #DigitalTransformation# #EmergingTechnology# #TechStartups# #Industry40#

The future of humanoids isn't just mechanical—it's neural. A humanoid robot is an embodied AI system. Motors, sensors, and actuators provide the body, but neural intelligence provides the mind. Neural models power vision, speech, language, navigation, manipulation, planning, memory, decision-making, and continuous learning. As robotics evolves, nearly every cognitive subsystem is becoming neural-first. That's why represents more than a niche—it's a foundational concept for the next generation of intelligent robotics. #HumanoidRobots# #EmbodiedAI# #PhysicalAI# #NeuralNetworks# #ArtificialIntelligence# #Robotics# #MachineLearning# #DeepLearning# #RobotLearning# #ReinforcementLearning# #ComputerVision# #GenerativeAI# #AIResearch# #Automation# #FutureOfAI#

Collaborative robots ("cobots") are reshaping the future of work by augmenting human capabilities—not replacing them. Designed to safely work alongside people, cobots are transforming manufacturing today and arerapidly expanding into healthcare, logistics, agriculture, laboratories, construction, and retail. As AI, machine vision, and semantic reasoning continue to evolve, cobots will becomeincreasingly adaptive, autonomous, and interconnected. Their future depends not only on physical intelligence, but also onstandardized digital identities, interoperable data, and shared semantic understandingacross global ecosystems. In Web3, domain namespaces such as .COBOTS have the potential to serve as digital identity infrastructure for robotics ecosystems—supporting decentralized identities, machine-readable services, asset discovery, and trusted interactions between robots, organizations, developers, and AI agents. Web3 domains are increasingly being explored as a foundation for digital identity and decentralized applications. #Cobots# #CollaborativeRobots# #Robotics# #Web3# #DigitalIdentity# #AI# #Industry40# #Industry50# #HumanoidRobots# #SemanticWeb# #KnowledgeGraph# #Automation# #FutureOfWork#

The next trillion-dollar industry won't just be AI. It will be AI Humanoids + Web3 + DigitalIdentity. Explore .humanoids: Here's why: 1/ AI has transformed software. The next transformation is physical. Humanoid robots are moving into manufacturing, warehouses, healthcare, logistics, retail, and eventually everyday life. Some long-term industry forecasts envisionthe humanoid robotics economy reaching themulti-trillion-dollar range over the coming decades. 2/ Intelligence alone isn't enough. Autonomous humanoids will need secure digital identities to interact with people, businesses, and other machines. Identity becomes infrastructure. 3/ They'll also need to:
• Verify who they are
• Own digital assets
• Build reputation
• Authenticate services
• Access decentralized networks
• Coordinate with other AI agents 4/ That's where Web3 can add value. Decentralized identity, ownership, programmable payments, and verifiable credentials can enable machine-to-machine interactions without depending on a single centralized authority. 5/ As this ecosystem grows, human-readabledigital identities become increasingly important. Owning a .humanoids digital identity today could be similar to securing premium internetreal estate before mass adoption—givingbuilders, brands, creators, and communities anearly presence in the emerging humanoid economy. 6/ AI gives humanoids intelligence. Web3 enables ownership and verifiable identity. Together, they could help support autonomousmachine economies. 7/ The future won't just be digital. It may walk beside us. Work alongside us. And interact with us every day. We're still early. Discover the future of .humanoids:
 What role do you think decentralized identity will play in the age of autonomous robots? 👇 Join the discussion. #Humanoids# #AI# #Web3# #Robotics##DigitalIdentity# #ArtificialIntelligence##MachineEconomy# #FutureOfWork##Automation# #Blockchain# #DePIN#

After 3-4 months of iteration, Open Minis — "possibly the best Agent app on your phone" — has stabilized into a mature architecture, now powering tens of thousands of users' daily workflows. Today we're open sourcing all of it: the full iOS and Android code. A real on-device AI agent: a native Linux shell, browser automation, extensible skills, persistent memory, and deep system integration. Now, fork it, feel free to build your own on-device agent now. 🤗

From a legacy of innovation to a future powered by automation: @Honeywell Technologies rang the Nasdaq closing bell at its Charlotte, North Carolina headquarters. Catch the highlights from the celebration. $HON #NasdaqListed#

卧槽？？？？tmd这次 @claudeai 把牙膏挤爆了🤯！！！ Anthropic刚刚发布Claude Opus 5。 以拉爆Claude Fable 5的前沿能力，价格直接来到Fable的一半。 Opus 5的API价格是每百万Token输入5美元、输出25美元，和Opus 4.8完全相同。 Fable 5则是10美元和50美元。 Anthropic直接把它定义为一款可以每天使用的高端模型，并将其设为Claude Max默认模型、Claude Pro最强模型。 跑分方面在CursorBench 3.2中，Opus 5开启最高Effort后，成绩只比Fable 5峰值低0.5%，但单任务成本只有后者一半。 在Frontier-Bench上，它以更低的单任务成本，将Opus 4.8的成绩提升到两倍以上。 Anthropic称，Opus 5目前已经在Frontier-Bench和GDPval-AA等编程、知识工作评测中达到SOTA。 Agent和电脑操作的提升更夸张，同时ARC-AGI 3成绩是第二名的3倍。。。 Zapier AutomationBench中，同等成本下通过率约为第二名的1.5倍，即使使用最低Effort，完成的任务也比其他模型更多。 OSWorld 2.0中，Opus 5只花Fable 5略高于三分之一的成本，就超过了Fable 5的最好成绩。 但这次最值得关注的，可能还不是跑分。 Anthropic反复强调Opus 5更擅长验证自己的工作，并持续迭代到任务真正完成。 一个测试里，模型拿不到机械零件原图，只能访问原始像素。Opus 5自己写了一套计算机视觉管线，提取几何结构，最后在FreeCAD中重建出了完整零件。 另一个任务中，它发现没有实时数据流可以验证代码，于是顺手给自己搭了一套测试框架。 这是一种很关键的Agent能力：发现当前环境缺少完成任务所需的工具，然后自己创造工具。 Opus 5同时加入了Fast Mode，速度大约是默认模式的2.5倍，价格是基础版本的两倍。 API模型名为claude-opus-5，目前已经登陆Claude、Claude Code、Claude Cowork和Claude Platform。 Anthropic现在的模型分层也越来越清楚： Sonnet负责规模和成本； Opus负责绝大部分高难度日常工作； Fable和Mythos继续探索能力与高风险领域的最前沿。 Opus 5真正的场景是大量编程、研究、数据分析和Agent任务，它正在让用户很难继续为Fable 5支付两倍价格。 前沿模型开始主动下放能力、压低价格。 模型战争接下来的重点，会从谁的能力上限最高，逐渐变成谁能用更低成本，把任务稳定地做完。 牛逼，看来前段时间 @OpenAI 和中国开源模型们（ @Kimi_Moonshot 和 @Zai_org ）真的给A/太多压力了！ 继续加油啊家人们！

“Nasdaq is home for innovative companies and I’m really proud we are able to join that cohort as Honeywell Technologies.” @Honeywell Technologies CEO Vimal Kipur takes the Nasdaq podium as $HON starts a new era as a pure-play automation leader.

After spinning off Honeywell Aerospace, @Honeywell Technologies is celebrating the beginning of a new era. As a pure-play automation leader helping solve some of the world’s most complex industrial challenges, the company is building on a legacy of innovation while shaping what’s next. Proud to mark this milestone with $HON. #NasdaqListed#