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OpenClaw

委托任务、调研与成果交付

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近 7 天的 49 条评论中,评价褒贬并存。批评最集中在「稳定性」(9/19 条负面摘录)。有用户升级OpenClaw过程顺利,所有cron任务都成功保留。有用户花了两天试图从9.4升级到9.6,多次触及限制,感到厌倦。

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23 条评价摘录

负面工作流与集成

花了两天时间试图从9.4升级到9.6,期间几次触及限制。这变得越来越令人厌烦

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Spent two days trying to get from 9.4 to 9.6 hitting my limits a couple of times. It's getting tiresome

负面编辑与控制

它是支持的,但我需要继承之前的白名单——我不得不在openclaw.json的modelPolicy.allow中允许gpt6模型的allowlist。

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It’s supported but carrying over my previous whitelist - I had to allow the gpt6 models allowlist in the openclaw. json modelPolicy.allow

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6.1-sol还不支持吗?

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6.1-sol isn’t supported yet?

负面编辑与控制

预算检查应该在调度之前预留支出,而不是在并行工作已经消耗完额度之后每小时检查一次。

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Budget checks should reserve spend before dispatch, not inspect it hourly after parallel work has already consumed the allowance.

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设置了一个循环,让我的OpenClaw尽可能自主运行,同时每小时检查订阅限制(对我来说这是OpenAI,但你可以调整为你想要的任何服务)。 Main将项目分配给项目经理子代理。 Main给自己设置每小时cron任务提醒来检查订阅使用情况,低于20%时暂停所有项目和提醒,并设置新的提醒以便在限制重置时恢复。

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Made a loop my OpenClaw become as autonomous as possible while hourly checking subscription limits (for me it's OpenAI but you can adjust it to whatever you want). Main assigns projects to a Project Manager sub-agent. Main puts hourly cron job reminders to herself to check subscription use, below 20% pauses all projects and reminders, sets new reminder to resume when limit resets.

负面编辑与控制

在我们的设置中(OpenClaw 2026.9.5),代理在工具调用之前或之间写的文本会作为消息在心跳和隔离的cron运行中传递,而不仅仅是最终答案。NO_REPLY只有在整个回复恰好是那一个token时才抑制传递。所以"重述请求,决定是否回答,NO_REPLY"会完整发出。

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In our setup (OpenClaw 2026.9.5), text an agent writes before or between tool calls gets delivered as a message in heartbeat and isolated cron runs, not just the final answer. And NO_REPLY only suppresses delivery when the entire reply is exactly that one token. So "restate the request, decide whether to answer, NO_REPLY" goes out in full.

负面工作流与集成

我注意到当你在 openclaw 中选择 Claude 作为模型时,会话运行 Claude code,所有子代理也在 Claude code 中运行。

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I’ve noticed that when you select Claude as the model in openclaw that the session runs Claude code and all the subagents run in Claude code. You can tell because Claude doesn’t get affected by the agent instructions and instead follows its Claude code rules.

负面编辑与控制

而且它还是个多管闲事的家伙,总是想办法查看过去的会话数据。

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And it’s a nosy bastard too finding lots of reasons to look through past session data.

负面效果与质量

我受够了这些层出不穷的bug,索性在全新的Ubuntu虚拟机上开始操作,让claude指向我备份的旧仓库里的OC项目,然后说"我需要这个功能、那个功能,还有这个..."它就开始从零开始帮我构建所需的一切。

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I got tired of the roller coaster of bugs and just started on a new clean Ubuntu VM, pointed claude at my old repo backup of my OC and said "I want this feature, that feature, and this..." and it started building me from scratch whatever I needed.

负面稳定性

不会因为膨胀而在一天或一周后突然忘记什么,效率非常高。

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No forgetting a day or week later suddenly due to bloat, it is just very efficient.

负面价格与额度

按小时运行的定时任务消耗了太多用量

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hourly crons eats up too much of my usage

负面稳定性

只是我早期用OpenClaw时它每天都在坏,但我不指望Muse也会这样

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Its just I used OpenClaw early on when it constantly broke every day but I'm not expecting that from muse

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Muse可能由OpenClaw驱动,但没关系 我想使用Muse最好的好处是能访问模型和大量的token配额

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Muse is probably powered by OpenClaw but thats okay i suppose the best benefit of using muse will be access to the model and a big token allowance

负面速度

OpenClaw对我来说太慢了。 已经不用了。

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Open claw was too slow for me. Retired.

负面工作流与集成

问题在于计费方式:消费者套餐使用滚动时间窗口计费,这是为交互式使用设计的,而一个整天循环调用工具的代理不到一小时就会耗尽重置额度。

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The catch is metering: consumer plans meter with rolling time windows built for interactive use, and an agent that loops tool calls all day drains a fresh reset in under an hour.

负面易用性

我学到的是不要依赖GUI,要用HTTP或CLI。在本地模型上运行任何任务之前,创建一个preflight skill来确保集群稳定。我没有时间再次测试,但使用GUI充其量是模糊的。它会丢失拓扑跟踪,CLI/HTTP比GUI更权威。

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What I’ve learned is don’t rely on the GUI and use HTTP or CLI instead. Create a preflight skill to make sure the cluster is stable before running any missions on the local model. I haven’t had time to test it again but using the GUI is ambiguous at best. Loses track of topology and the CLI/HTTP are more authoritative than the GUI.

负面稳定性

我很好奇是什么让人们想用这个软件,因为我看到的帖子都是说一次更新毁掉了他们辛苦工作的一切...

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I'm curious about what makes ppl want to use this software when all I see are posts that an update broke everything they worked hard on...

负面稳定性

然后我会再次等待最稳定的版本

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And then i will wait for the most stable release again

负面稳定性

自六月以来升级真的很麻烦。试过几次,每次都得回滚。

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I had real trouble with upgrades since June. Tried a few times and had to roll back every time.

负面稳定性

昨晚我不得不强行完成更新。我的数据库比较大,有6GB。不知道为什么,更新过程会把数据库在内存里复制三份。我不得不把VM的内存加到24GB,然后增加swap空间才能完成更新。很奇怪的过程,但我终于搞定了。

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I had to force my way through the update last night. My database is fairly large at 6 GB. For some reason, the update process makes three copies of the database to ram. I had to increase the ram on my VM to 24 GB and then increase the swap for the update to be able to take place. Very odd process, but I finally got there.

负面易用性

我根本无法升级。

机器翻译
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I cannot even upgrade.

负面稳定性

我有一个openclaw-ops技能,现在默认会在做任何事情之前先检查github issues,因为确实大多数时候当某些东西不工作时,我们遇到的bug已经有对应的issue存在了。

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I have an openclaw-ops skill that will now by default check github issues before we do anything because sure enough most of the time something doesnt work, we hit a bug for which an issue already exists.

负面稳定性工作流与集成

我不得不在其中加入心跳系统,但我比喜欢open claw更喜欢它。

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I've had to build a heartbeat system into them but I love it way more than open claw.

负面稳定性

9.6让我切换到了Hermes,我真希望自己早点这么做。

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9.6 made me switch to Hermes and I wish I'd done it sooner.

负面价格与额度

所以他们把一个请求变成了三个,还以为习惯直接调用的模型会神奇地理解这种新方式,而不是茫然无措并浪费积分。他们是嗑药了吗?他们以为我们都是用钱做的吗?

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So they turned one request into three, and assumed that models used to direct calls will magically understand this new way of doing things instead of floundering and wasting credits. Are they high? Do they think we're all made of money?

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OpenClaw现在默认启用了“tool search”功能。代理现在必须使用tool search工具来查找他们想使用的工具,然后使用tool describe来描述工具及其使用方法,再使用tool call工具来调用工具。

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Openclaw now has “tool search” enabled by default. Agents now have to use the tool search tool, to find matches for the tools they want to use, then use tool describe to describe the tool and how to use it, and then they use the tool call tool to call a tool.

负面工作流与集成

所以他们把一个请求变成了三个,还以为习惯直接调用的模型会神奇地理解这种新方式,而不是茫然无措并浪费积分。

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So they turned one request into three, and assumed that models used to direct calls will magically understand this new way of doing things instead of floundering and wasting credits.

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代理现在必须使用tool search工具来查找他们想使用的工具,然后使用tool describe来描述工具及其使用方法,再使用tool call工具来调用工具。

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Agents now have to use the tool search tool, to find matches for the tools they want to use, then use tool describe to describe the tool and how to use it, and then they use the tool call tool to call a tool.