{"type":"session","version":3,"id":"da138ffe-66e4-4f06-b80f-d4fe46f79f06","timestamp":"2026-05-23T06:32:30.849Z","cwd":"/root/.openclaw/workspace/fabu"}
{"type":"model_change","id":"8e51c434","parentId":null,"timestamp":"2026-05-23T06:32:30.858Z","provider":"deepseek","modelId":"deepseek-chat"}
{"type":"thinking_level_change","id":"8a804e9b","parentId":"8e51c434","timestamp":"2026-05-23T06:32:30.858Z","thinkingLevel":"off"}
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{"type":"message","id":"0b42a15a","parentId":"7df6cddb","timestamp":"2026-05-23T06:32:30.929Z","message":{"role":"user","content":[{"type":"text","text":"[Sat 2026-05-23 14:32 GMT+8] [Subagent Context] You are running as a subagent (depth 1/1). Results auto-announce to your requester; do not busy-poll for status.\n\nBegin. Your assigned task is in the system prompt under **Your Role**; execute it to completion."}],"timestamp":1779517950882}}
{"type":"message","id":"d6ef0634","parentId":"0b42a15a","timestamp":"2026-05-23T06:32:33.113Z","message":{"role":"assistant","content":[{"type":"text","text":"Let me start by examining the required files to understand what I'm working with."},{"type":"toolCall","id":"call_00_2IZswkI3dMa7wQYFozl06436","name":"read","arguments":{"path":"/root/.openclaw/agents/101/workspace/post-to-wechat/2026-05-23/DeepSeek-V4Pro-降价-2026-05-23.md"}},{"type":"toolCall","id":"call_01_7cHcqg9JOiR8knlE0E2q3086","name":"read","arguments":{"path":"/root/.openclaw/agents/文章大师/workspace/deepseek-permanent-price-cut-20260523-v1.md"}},{"type":"toolCall","id":"call_02_DacaiJz2hsM2VufFC8iS3682","name":"read","arguments":{"path":"/root/.openclaw/agents/101/workspace/ads-image-map.json"}}],"api":"openai-completions","provider":"deepseek","model":"deepseek-chat","usage":{"input":5241,"output":200,"cacheRead":7168,"cacheWrite":0,"totalTokens":12609,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"toolUse","timestamp":1779517950929,"responseId":"4d5b2cd1-c48f-476d-acf5-c4fc31294f72"}}
{"type":"message","id":"1740cdc2","parentId":"d6ef0634","timestamp":"2026-05-23T06:32:33.383Z","message":{"role":"toolResult","toolCallId":"call_00_2IZswkI3dMa7wQYFozl06436","toolName":"read","content":[{"type":"text","text":"\n# 不是促销，是屠刀：DeepSeek 把 API 价格永久砍掉 75%，整个行业被迫接招\n\n想象你是某家AI创业公司的CTO。\n\n5月22日下午，你像往常一样打开 DeepSeek 官网，准备查一下 V4 Pro 的 API 定价。结果你愣住了：之前打2.5折的促销价，5月31日之后，直接变成永久正价。不是\"限时特惠\"，不是\"新用户福利\"。是官方主页上白纸黑字写着——降价75%，永久执行。\n\n你第一反应是什么？不是\"DeepSeek真大方\"。而是\"卧槽，那我的产品定价和商业模型要重新算了\"。\n\n这才是这则消息真正的杀伤力。\n\n## 这招，比技术突破还狠\n\n很多人的第一反应是：DeepSeek V4 Pro 又降价了？哦，促销活动而已。\n\n再看一眼。\n\n5月22日，DeepSeek 官方更新了 API 定价页面。清晰明确：deepseek-v4-pro 模型价格在结束2.5折优惠活动后，正式调整为原价的1/4。**不是临时活动延续，而是永久性的标价调整。**\n\n翻译成人话：**促销价变成了常规价。** 之前你以为\"薅羊毛\"的窗口，现在变成了永久通道。\n\n这跟所有AI公司的套路都不一样。\n\nOpenAI、Google、Anthropic 都搞过降价。但它们的模式是\"限时优惠\"——给新用户送额度、推出轻量版降价、或者搞\"首月半价\"。本质上是**营销战术**，不是定价战略。优惠期一过，价格恢复原样，开发者老老实实继续交钱。\n\nDeepSeek 的做法完全反着来：把打折变成正价，把促→销变成永久降价。这意味着什么？\n\n**它的成本已经低到不需要\"恢复原价\"了。**\n\n这话如果从别人嘴里说出来，你可能不信。但 DeepSeek 从 V2 到 V4 Pro，价格一直在降，从未涨过。每一次降价都不是\"为了抢客户烧钱\"，而是技术优化后成本下降了，自然传导给用户。\n\n这次更狠——直接一刀剁掉 75%。\n\n## 跟 GPT-5.5 比，已经不是竞争，是屠杀\n\n做AI应用的朋友都清楚一个问题：\n\nAPI 调用成本，从来不是\"用不用得起\"的问题，而是\"能不能撑起商业模型\"的问题。\n\n举个最简单的例子：假设你的AI应用，每次用户提问需要调用大模型生成回答。用 GPT-5.5，输出的边际成本是 X 元。用 DeepSeek V4 Pro，成本是 X 除以几十。\n\n如果你的应用是高频交互型的——比如AI客服、AI助手、AI教育——那几十倍的成本差距，直接决定了你的定价策略和利润空间能用多大的分水岭。\n\nGPT-5.5 用户每次对话你赚1毛，GPT-5.5 用户每次对话亏8分——成本差异就能把一条业务线从赚钱变成亏钱。\n\n而 DeepSeek V4 Pro 的降价，相当于把所有用GPT-5.5做应用的创业者都推到了一个选择题面前：**要么换平台，成本降到原来的几十分之一；要么保持现状，眼睁睁看对手用更低的成本抢你的客户。**\n\n听起来残酷，但商业就是这样。\n\n## 摩尔定律在大模型时代的变体\n\n你可能要问：DeepSeek 凭什么能做到这么低的价格？\n\n答案不是什么\"中国公司人工便宜\"，而是**全栈优化的累积效应**。\n\n摩尔定律的历史告诉我们：芯片性能每18个月翻一倍，成本降一半。但那是硬件端的规律。\n\n大模型的成本下降，吃的是三块红利：\n\n第一块，**模型架构层面的优化。** DeepSeek 自研的 MoE（混合专家）架构，让每次推理只激活部分参数，不像 GPT-5.5 那样的稠密模型每问一次全量计算。这就好比开一盏灯，不用点亮整栋楼。\n\n第二块，**训练-推理一体化。** 很多AI公司的训练和推理是分离的团队、分离的架构。DeepSeek 从模型设计那天就考虑推理效率。训练阶段做的优化在推理阶段也能复用，效率叠加。\n\n第三块，**部署层优化。** 从底层算子到硬件调度，DeepSeek 的工程团队把每一层都做精了。看起来是\"降价75%\"的激进定价，背后是每一层的成本都砍了一刀。\n\n**只有真正掌控了从模型架构→训练→推理→部署全栈的公司，才能把降价转嫁给用户。**\n\n大多数AI公司要么只有模型层能力（研发强，工程弱），要么只有应用层能力（调API，不懂底层）。DeepSeek的可怕之处在于：它把整个链条都打通了，然后选择了一个最暴力的打法——价格战。\n\n## 给创业者的信号：之前的借口，现在都不成立了\n\n说实话，过去一年我跟不少做AI应用的人聊过。\n\n聊到为什么产品做得慢、为什么用户量上不去，十个里有七八个会说：\"没办法，API成本太高，跑不起大规模。\"\n\n这个借口，现在彻底废了。\n\nDeepSeek V4 Pro 把旗舰模型的价格打到了白菜价。按新的定价，你用它搭一个AI产品，边际成本已经低到可以忽略不计。以前\"API太贵\"是真实的障碍，现在这个障碍已经被铲平了。\n\n这意味着什么？\n\n**AI应用层的创业逻辑，需要重新写。** 以前大家拼的是\"谁能烧得起推理成本\"。以后拼的是\"谁能做出用户真正想用的东西\"。\n\n场景创新、产品体验、用户留存——这些被成本问题压了两年的话题，现在可以真正提上日程了。\n\n如果你是一个做AI应用的创业者，现在最好的策略不是继续观望等下一轮降价。是立刻上手，用这个价格去验证你的商业模式。因为当API成本不再是天花板，你的天花板就是你的产品和运营能力。\n\n## 整个行业，被迫接招\n\nDeepSeek 这一刀，不只是打给开发者和企业看的。这一刀，是砍给整个AI行业看的。\n\nOpenAI、Google、Anthropic 现在面临一个两难选择：\n\n**要么跟牌降价，利润更薄。**\n\nGPT-5.5 的训练和推理成本结构跟 DeepSeek V4 Pro 完全不同。DeepSeek 是用 MoE 架构、全栈优化、以及相对更低的人力成本在支撑定价。OpenAI 想降到同样价位，要么压缩自己的利润空间，要么做更大的架构创新。两条路都不轻松。\n\n**要么不做降价，押注差异化。**\n\n赌的是\"品牌溢价\"、\"安全性\"、\"企业级服务\"这些DeepSeek比较薄弱的环节。不是不行，但前提是你得有足够多的企业客户愿意为这些溢价买单。当隔壁家便宜了几十倍，很多技术决策者会在董事会上被老板问：\"为什么我们不能用那个更便宜的？\"\n\n这场景，像极了当年的云计算价格战。AWS、Azure、Google Cloud 轮流降价，每个季度都比上个季度低一点。你降，他降，最后大家都降。\n\n但 DeepSeek 这次不是\"降一点\"，是直接降了四分之三。\n\n这已经不是在打价格战了。这是在重新定义\"公允价格\"。\n\n当整个行业的参考价被一家公司腰斩再腰斩，其他公司要么跟上，要么退到小众市场。没有中间地带。\n\n## 时间节点，是精心算过的\n\n5月22日发布，5月31日生效。\n\n一周时间。\n\n看起来是一个\"给用户过渡期\"，但仔细想想，这一周对DeepSeek来说，信息价值极大。\n\n5月22日到5月31日这7天，所有正在用GPT-5.5或者其他模型的企业，会怎么做？\n\n- 预算部门会算账：换成DeepSeek能省多少钱\n- 技术部门会测试：迁移需要多少工作量\n- 决策部门会开会：要不要换供应商\n\nDeepSeek 给了他们一周时间算这笔账。它不怕你算。它希望你算。\n\n因为不管你怎么算，结果都是：换过来，省一大笔钱。\n\n这7天，也是DeepSeek收割市场信号的窗口期。哪些企业最着急迁移，哪些行业对成本最敏感，哪些客户群体会跟着降价迁移——这些信息在7天后的定价生效日，会全部暴露。\n\n这不是一个简单的\"我们降价了\"的通知。这是一次精心设计的市场渗透行动。\n\n---\n\n回到开头那个CTO的视角。\n\n当他缓过神来，拿起手机在群里发了一句：\"DeepSeek 这轮降价后，我们用什么理由继续用GPT-5.5？\"\n\n群里沉默了三秒，然后有人回了一句：\n\n\"没有理由了。\"\n\n这就是 DeepSeek 真正的胜利。不是你做不出更好的模型，而是你让所有用户都找不到继续用你的理由。\n\n一刀 75%，砍掉的不是价格。是竞争对手的市场防守底线。\n\n---\n\n![广告海报](/root/imgs/ads/OPC一人公司/1.jpg)\n"}],"isError":false,"timestamp":1779517953383}}
{"type":"message","id":"11bda6e1","parentId":"1740cdc2","timestamp":"2026-05-23T06:32:33.384Z","message":{"role":"toolResult","toolCallId":"call_01_7cHcqg9JOiR8knlE0E2q3086","toolName":"read","content":[{"type":"text","text":"---\ncover_category: ai-robot\ndomain: weixinsiwei.com\n---\n\n# 不是促销，是屠刀：DeepSeek 把 API 价格永久砍掉 75%，整个行业被迫接招\n\n想象你是某家AI创业公司的CTO。\n\n5月22日下午，你像往常一样打开 DeepSeek 官网，准备查一下 V4 Pro 的 API 定价。结果你愣住了：之前打2.5折的促销价，5月31日之后，直接变成永久正价。不是\"限时特惠\"，不是\"新用户福利\"。是官方主页上白纸黑字写着——降价75%，永久执行。\n\n你第一反应是什么？不是\"DeepSeek真大方\"。而是\"卧槽，那我的产品定价和商业模型要重新算了\"。\n\n这才是这则消息真正的杀伤力。\n\n## 这招，比技术突破还狠\n\n很多人的第一反应是：DeepSeek V4 Pro 又降价了？哦，促销活动而已。\n\n再看一眼。\n\n5月22日，DeepSeek 官方更新了 API 定价页面。清晰明确：deepseek-v4-pro 模型价格在结束2.5折优惠活动后，正式调整为原价的1/4。**不是临时活动延续，而是永久性的标价调整。**\n\n翻译成人话：**促销价变成了常规价。** 之前你以为\"薅羊毛\"的窗口，现在变成了永久通道。\n\n这跟所有AI公司的套路都不一样。\n\nOpenAI、Google、Anthropic 都搞过降价。但它们的模式是\"限时优惠\"——给新用户送额度、推出轻量版降价、或者搞\"首月半价\"。本质上是**营销战术**，不是定价战略。优惠期一过，价格恢复原样，开发者老老实实继续交钱。\n\nDeepSeek 的做法完全反着来：把打折变成正价，把促→销变成永久降价。这意味着什么？\n\n**它的成本已经低到不需要\"恢复原价\"了。**\n\n这话如果从别人嘴里说出来，你可能不信。但 DeepSeek 从 V2 到 V4 Pro，价格一直在降，从未涨过。每一次降价都不是\"为了抢客户烧钱\"，而是技术优化后成本下降了，自然传导给用户。\n\n这次更狠——直接一刀剁掉 75%。\n\n## 跟 GPT-5.5 比，已经不是竞争，是屠杀\n\n做AI应用的朋友都清楚一个问题：\n\nAPI 调用成本，从来不是\"用不用得起\"的问题，而是\"能不能撑起商业模型\"的问题。\n\n举个最简单的例子：假设你的AI应用，每次用户提问需要调用大模型生成回答。用 GPT-5.5，输出的边际成本是 X 元。用 DeepSeek V4 Pro，成本是 X 除以几十。\n\n如果你的应用是高频交互型的——比如AI客服、AI助手、AI教育——那几十倍的成本差距，直接决定了你的定价策略和利润空间能用多大的分水岭。\n\nGPT-5.5 用户每次对话你赚1毛，GPT-5.5 用户每次对话亏8分——成本差异就能把一条业务线从赚钱变成亏钱。\n\n而 DeepSeek V4 Pro 的降价，相当于把所有用GPT-5.5做应用的创业者都推到了一个选择题面前：**要么换平台，成本降到原来的几十分之一；要么保持现状，眼睁睁看对手用更低的成本抢你的客户。**\n\n听起来残酷，但商业就是这样。\n\n## 摩尔定律在大模型时代的变体\n\n你可能要问：DeepSeek 凭什么能做到这么低的价格？\n\n答案不是什么\"中国公司人工便宜\"，而是**全栈优化的累积效应**。\n\n摩尔定律的历史告诉我们：芯片性能每18个月翻一倍，成本降一半。但那是硬件端的规律。\n\n大模型的成本下降，吃的是三块红利：\n\n第一块，**模型架构层面的优化。** DeepSeek 自研的 MoE（混合专家）架构，让每次推理只激活部分参数，不像 GPT-5.5 那样的稠密模型每问一次全量计算。这就好比开一盏灯，不用点亮整栋楼。\n\n第二块，**训练-推理一体化。** 很多AI公司的训练和推理是分离的团队、分离的架构。DeepSeek 从模型设计那天就考虑推理效率。训练阶段做的优化在推理阶段也能复用，效率叠加。\n\n第三块，**部署层优化。** 从底层算子到硬件调度，DeepSeek 的工程团队把每一层都做精了。看起来是\"降价75%\"的激进定价，背后是每一层的成本都砍了一刀。\n\n**只有真正掌控了从模型架构→训练→推理→部署全栈的公司，才能把降价转嫁给用户。**\n\n大多数AI公司要么只有模型层能力（研发强，工程弱），要么只有应用层能力（调API，不懂底层）。DeepSeek的可怕之处在于：它把整个链条都打通了，然后选择了一个最暴力的打法——价格战。\n\n## 给创业者的信号：之前的借口，现在都不成立了\n\n说实话，过去一年我跟不少做AI应用的人聊过。\n\n聊到为什么产品做得慢、为什么用户量上不去，十个里有七八个会说：\"没办法，API成本太高，跑不起大规模。\"\n\n这个借口，现在彻底废了。\n\nDeepSeek V4 Pro 把旗舰模型的价格打到了白菜价。按新的定价，你用它搭一个AI产品，边际成本已经低到可以忽略不计。以前\"API太贵\"是真实的障碍，现在这个障碍已经被铲平了。\n\n这意味着什么？\n\n**AI应用层的创业逻辑，需要重新写。** 以前大家拼的是\"谁能烧得起推理成本\"。以后拼的是\"谁能做出用户真正想用的东西\"。\n\n场景创新、产品体验、用户留存——这些被成本问题压了两年的话题，现在可以真正提上日程了。\n\n如果你是一个做AI应用的创业者，现在最好的策略不是继续观望等下一轮降价。是立刻上手，用这个价格去验证你的商业模式。因为当API成本不再是天花板，你的天花板就是你的产品和运营能力。\n\n## 整个行业，被迫接招\n\nDeepSeek 这一刀，不只是打给开发者和企业看的。这一刀，是砍给整个AI行业看的。\n\nOpenAI、Google、Anthropic 现在面临一个两难选择：\n\n**要么跟牌降价，利润更薄。**\n\nGPT-5.5 的训练和推理成本结构跟 DeepSeek V4 Pro 完全不同。DeepSeek 是用 MoE 架构、全栈优化、以及相对更低的人力成本在支撑定价。OpenAI 想降到同样价位，要么压缩自己的利润空间，要么做更大的架构创新。两条路都不轻松。\n\n**要么不做降价，押注差异化。**\n\n赌的是\"品牌溢价\"、\"安全性\"、\"企业级服务\"这些DeepSeek比较薄弱的环节。不是不行，但前提是你得有足够多的企业客户愿意为这些溢价买单。当隔壁家便宜了几十倍，很多技术决策者会在董事会上被老板问：\"为什么我们不能用那个更便宜的？\"\n\n这场景，像极了当年的云计算价格战。AWS、Azure、Google Cloud 轮流降价，每个季度都比上个季度低一点。你降，他降，最后大家都降。\n\n但 DeepSeek 这次不是\"降一点\"，是直接降了四分之三。\n\n这已经不是在打价格战了。这是在重新定义\"公允价格\"。\n\n当整个行业的参考价被一家公司腰斩再腰斩，其他公司要么跟上，要么退到小众市场。没有中间地带。\n\n## 时间节点，是精心算过的\n\n5月22日发布，5月31日生效。\n\n一周时间。\n\n看起来是一个\"给用户过渡期\"，但仔细想想，这一周对DeepSeek来说，信息价值极大。\n\n5月22日到5月31日这7天，所有正在用GPT-5.5或者其他模型的企业，会怎么做？\n\n- 预算部门会算账：换成DeepSeek能省多少钱\n- 技术部门会测试：迁移需要多少工作量\n- 决策部门会开会：要不要换供应商\n\nDeepSeek 给了他们一周时间算这笔账。它不怕你算。它希望你算。\n\n因为不管你怎么算，结果都是：换过来，省一大笔钱。\n\n这7天，也是DeepSeek收割市场信号的窗口期。哪些企业最着急迁移，哪些行业对成本最敏感，哪些客户群体会跟着降价迁移——这些信息在7天后的定价生效日，会全部暴露。\n\n这不是一个简单的\"我们降价了\"的通知。这是一次精心设计的市场渗透行动。\n\n---\n\n回到开头那个CTO的视角。\n\n当他缓过神来，拿起手机在群里发了一句：\"DeepSeek 这轮降价后，我们用什么理由继续用GPT-5.5？\"\n\n群里沉默了三秒，然后有人回了一句：\n\n\"没有理由了。\"\n\n这就是 DeepSeek 真正的胜利。不是你做不出更好的模型，而是你让所有用户都找不到继续用你的理由。\n\n一刀 75%，砍掉的不是价格。是竞争对手的市场防守底线。\n"}],"isError":false,"timestamp":1779517953383}}
{"type":"message","id":"7346daf6","parentId":"11bda6e1","timestamp":"2026-05-23T06:32:33.384Z","message":{"role":"toolResult","toolCallId":"call_02_DacaiJz2hsM2VufFC8iS3682","toolName":"read","content":[{"type":"text","text":"{\n  \"OPC一人公司\": {\n    \"1.jpg\": \"https://weixinsiwei.com/zb_users/upload/2026/05/84850393b2efb63633d3fdfd9a6e21b4.jpg\",\n    \"2.jpg\": \"https://weixinsiwei.com/zb_users/upload/2026/05/768626af4d00cda9cd84199b70d7f880.jpg\"\n  }\n}\n"}],"isError":false,"timestamp":1779517953383}}
{"type":"message","id":"e4fb5e36","parentId":"7346daf6","timestamp":"2026-05-23T06:32:35.296Z","message":{"role":"assistant","content":[{"type":"text","text":"Good, I have all the info I need. Let me now check the wechat-api script and the md2html script exist."},{"type":"toolCall","id":"call_00_rqoeeird2ejaY0lpC2HA6117","name":"exec","arguments":{"command":"ls -la /root/.openclaw/skills/baoyu-post-to-wechat/scripts/wechat-api.ts"}},{"type":"toolCall","id":"call_01_0LRSLZ4MlmxEHbVEMGmM4327","name":"exec","arguments":{"command":"ls -la /root/.openclaw/agents/发布大师/workspace/scripts/md2html.py"}},{"type":"toolCall","id":"call_02_obR9Q6KO0rS6lhMG8oYr1614","name":"exec","arguments":{"command":"ls -la /root/.openclaw/agents/101/workspace/post-to-wechat/2026-05-23/imgs/deepseek-cover.jpg"}}],"api":"openai-completions","provider":"deepseek","model":"deepseek-chat","usage":{"input":4251,"output":209,"cacheRead":12288,"cacheWrite":0,"totalTokens":16748,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"toolUse","timestamp":1779517953384,"responseId":"57d477c4-8f33-4ee7-a8ae-d8a63ac33f11"}}
{"type":"message","id":"23f883f5","parentId":"e4fb5e36","timestamp":"2026-05-23T06:32:35.747Z","message":{"role":"toolResult","toolCallId":"call_00_rqoeeird2ejaY0lpC2HA6117","toolName":"exec","content":[{"type":"text","text":"ls: cannot access '/root/.openclaw/skills/baoyu-post-to-wechat/scripts/wechat-api.ts': No such file or directory\n\n(Command exited with code 2)"}],"details":{"status":"completed","exitCode":2,"durationMs":166,"aggregated":"ls: cannot access '/root/.openclaw/skills/baoyu-post-to-wechat/scripts/wechat-api.ts': No such file or directory\n\n(Command exited with code 2)","cwd":"/root/.openclaw/workspace/fabu"},"isError":false,"timestamp":1779517955747}}
{"type":"message","id":"a98ea35b","parentId":"23f883f5","timestamp":"2026-05-23T06:32:35.747Z","message":{"role":"toolResult","toolCallId":"call_01_0LRSLZ4MlmxEHbVEMGmM4327","toolName":"exec","content":[{"type":"text","text":"-rw-r--r-- 1 root root 2599 Apr 29 19:05 /root/.openclaw/agents/发布大师/workspace/scripts/md2html.py"}],"details":{"status":"completed","exitCode":0,"durationMs":122,"aggregated":"-rw-r--r-- 1 root root 2599 Apr 29 19:05 /root/.openclaw/agents/发布大师/workspace/scripts/md2html.py","cwd":"/root/.openclaw/workspace/fabu"},"isError":false,"timestamp":1779517955747}}
{"type":"message","id":"c6a2ff16","parentId":"a98ea35b","timestamp":"2026-05-23T06:32:35.747Z","message":{"role":"toolResult","toolCallId":"call_02_obR9Q6KO0rS6lhMG8oYr1614","toolName":"exec","content":[{"type":"text","text":"-rw-r--r-- 1 root root 243462 May 23 14:31 /root/.openclaw/agents/101/workspace/post-to-wechat/2026-05-23/imgs/deepseek-cover.jpg"}],"details":{"status":"completed","exitCode":0,"durationMs":260,"aggregated":"-rw-r--r-- 1 root root 243462 May 23 14:31 /root/.openclaw/agents/101/workspace/post-to-wechat/2026-05-23/imgs/deepseek-cover.jpg","cwd":"/root/.openclaw/workspace/fabu"},"isError":false,"timestamp":1779517955747}}
{"type":"message","id":"78e20835","parentId":"c6a2ff16","timestamp":"2026-05-23T06:32:37.202Z","message":{"role":"assistant","content":[{"type":"text","text":"The wechat-api.ts script doesn't exist at that path. Let me find it."},{"type":"toolCall","id":"call_00_QprHP32OIMr8yDAvn8CH2367","name":"exec","arguments":{"command":"find /root/.openclaw -name \"wechat-api.ts\" -o -name \"wechat-api.js\" 2>/dev/null | head -20"}},{"type":"toolCall","id":"call_01_BQctfhGhx3VdtOK2u9Mc0766","name":"exec","arguments":{"command":"find /root/.openclaw/skills -name \"wechat*\" 2>/dev/null | head -20"}}],"api":"openai-completions","provider":"deepseek","model":"deepseek-chat","usage":{"input":269,"output":146,"cacheRead":16640,"cacheWrite":0,"totalTokens":17055,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"toolUse","timestamp":1779517955748,"responseId":"b30d9656-3fc9-4667-893f-2ee9f39e51c8"}}
{"type":"message","id":"e687edbc","parentId":"78e20835","timestamp":"2026-05-23T06:32:37.683Z","message":{"role":"toolResult","toolCallId":"call_00_QprHP32OIMr8yDAvn8CH2367","toolName":"exec","content":[{"type":"text","text":"/root/.openclaw/workspace/fabu/wechat-api.ts\n/root/.openclaw/agents/101/workspace/skills/baoyu-post-to-wechat/scripts/wechat-api.ts\n/root/.openclaw/agents/101/workspace/wechat-agent-template/skills/baoyu-post-to-wechat/scripts/wechat-api.ts"}],"details":{"status":"completed","exitCode":0,"durationMs":332,"aggregated":"/root/.openclaw/workspace/fabu/wechat-api.ts\n/root/.openclaw/agents/101/workspace/skills/baoyu-post-to-wechat/scripts/wechat-api.ts\n/root/.openclaw/agents/101/workspace/wechat-agent-template/skills/baoyu-post-to-wechat/scripts/wechat-api.ts","cwd":"/root/.openclaw/workspace/fabu"},"isError":false,"timestamp":1779517957683}}
{"type":"message","id":"7d745ed0","parentId":"e687edbc","timestamp":"2026-05-23T06:32:37.684Z","message":{"role":"toolResult","toolCallId":"call_01_BQctfhGhx3VdtOK2u9Mc0766","toolName":"exec","content":[{"type":"text","text":"(no output)"}],"details":{"status":"completed","exitCode":0,"durationMs":22,"aggregated":"","cwd":"/root/.openclaw/workspace/fabu"},"isError":false,"timestamp":1779517957683}}
{"type":"message","id":"4616f59f","parentId":"7d745ed0","timestamp":"2026-05-23T06:32:38.983Z","message":{"role":"assistant","content":[{"type":"text","text":"Found it. Let me check this script to understand its usage."},{"type":"toolCall","id":"call_00_Bp6Ds1E6sOQS1atV0nik6835","name":"read","arguments":{"path":"/root/.openclaw/agents/101/workspace/skills/baoyu-post-to-wechat/scripts/wechat-api.ts"}}],"api":"openai-completions","provider":"deepseek","model":"deepseek-chat","usage":{"input":137,"output":84,"cacheRead":17024,"cacheWrite":0,"totalTokens":17245,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"toolUse","timestamp":1779517957685,"responseId":"05960460-758c-492a-b0e7-910b9df183a7"}}
{"type":"message","id":"4ed2bb59","parentId":"4616f59f","timestamp":"2026-05-23T06:32:39.090Z","message":{"role":"toolResult","toolCallId":"call_00_Bp6Ds1E6sOQS1atV0nik6835","toolName":"read","content":[{"type":"text","text":"import fs from \"node:fs\";\nimport path from \"node:path\";\nimport { spawnSync } from \"node:child_process\";\nimport { fileURLToPath } from \"node:url\";\nimport { loadWechatExtendConfig, resolveAccount, loadCredentials } from \"./wechat-extend-config.ts\";\n\ninterface AccessTokenResponse {\n  access_token?: string;\n  errcode?: number;\n  errmsg?: string;\n}\n\ninterface UploadResponse {\n  media_id: string;\n  url: string;\n  errcode?: number;\n  errmsg?: string;\n}\n\ninterface PublishResponse {\n  media_id?: string;\n  errcode?: number;\n  errmsg?: string;\n}\n\ninterface ImageInfo {\n  placeholder: string;\n  localPath: string;\n  originalPath: string;\n}\n\ninterface MarkdownRenderResult {\n  title: string;\n  author: string;\n  summary: string;\n  htmlPath: string;\n  contentImages: ImageInfo[];\n}\n\ntype ArticleType = \"news\" | \"newspic\";\n\ninterface ArticleOptions {\n  title: string;\n  author?: string;\n  digest?: string;\n  content: string;\n  thumbMediaId: string;\n  articleType: ArticleType;\n  imageMediaIds?: string[];\n  needOpenComment?: number;\n  onlyFansCanComment?: number;\n}\n\nconst TOKEN_URL = \"https://api.weixin.qq.com/cgi-bin/token\";\nconst UPLOAD_URL = \"https://api.weixin.qq.com/cgi-bin/material/add_material\";\nconst DRAFT_URL = \"https://api.weixin.qq.com/cgi-bin/draft/add\";\n\n\nasync function fetchAccessToken(appId: string, appSecret: string): Promise<string> {\n  const url = `${TOKEN_URL}?grant_type=client_credential&appid=${appId}&secret=***\n  const res = await fetch(url);\n  if (!res.ok) {\n    throw new Error(`Failed to fetch access token: ${res.status}`);\n  }\n  const data = await res.json() as AccessTokenResponse;\n  if (data.errcode) {\n    throw new Error(`Access token error ${data.errcode}: ${data.errmsg}`);\n  }\n  if (!data.access_token) {\n    throw new Error(\"No access_token in response\");\n  }\n  return data.access_token;\n}\n\nasync function uploadImage(\n  imagePath: string,\n  accessToken: string,\n  baseDir?: string\n): Promise<UploadResponse> {\n  let fileBuffer: Buffer;\n  let filename: string;\n  let contentType: string;\n\n  if (imagePath.startsWith(\"http://\") || imagePath.startsWith(\"https://\")) {\n    const response = await fetch(imagePath);\n    if (!response.ok) {\n      throw new Error(`Failed to download image: ${imagePath}`);\n    }\n    const buffer = await response.arrayBuffer();\n    if (buffer.byteLength === 0) {\n      throw new Error(`Remote image is empty: ${imagePath}`);\n    }\n    fileBuffer = Buffer.from(buffer);\n    const urlPath = imagePath.split(\"?\")[0];\n    filename = path.basename(urlPath) || \"image.jpg\";\n    contentType = response.headers.get(\"content-type\") || \"image/jpeg\";\n  } else {\n    const resolvedPath = path.isAbsolute(imagePath)\n      ? imagePath\n      : path.resolve(baseDir || process.cwd(), imagePath);\n\n    if (!fs.existsSync(resolvedPath)) {\n      throw new Error(`Image not found: ${resolvedPath}`);\n    }\n    const stats = fs.statSync(resolvedPath);\n    if (stats.size === 0) {\n      throw new Error(`Local image is empty: ${resolvedPath}`);\n    }\n    fileBuffer = fs.readFileSync(resolvedPath);\n    filename = path.basename(resolvedPath);\n    const ext = path.extname(filename).toLowerCase();\n    const mimeTypes: Record<string, string> = {\n      \".jpg\": \"image/jpeg\",\n      \".jpeg\": \"image/jpeg\",\n      \".png\": \"image/png\",\n      \".gif\": \"image/gif\",\n      \".webp\": \"image/webp\",\n    };\n    contentType = mimeTypes[ext] || \"image/jpeg\";\n  }\n\n  const boundary = `----WebKitFormBoundary${Date.now().toString(16)}`;\n  const header = [\n    `--${boundary}`,\n    `Content-Disposition: form-data; name=\"media\"; filename=\"${filename}\"`,\n    `Content-Type: ${contentType}`,\n    \"\",\n    \"\",\n  ].join(\"\\r\\n\");\n  const footer = `\\r\\n--${boundary}--\\r\\n`;\n\n  const headerBuffer = Buffer.from(header, \"utf-8\");\n  const footerBuffer = Buffer.from(footer, \"utf-8\");\n  const body = Buffer.concat([headerBuffer, fileBuffer, footerBuffer]);\n\n  const url = `${UPLOAD_URL}?access_token=***&type=image`;\n  const res = await fetch(url, {\n    method: \"POST\",\n    headers: {\n      \"Content-Type\": `multipart/form-data; boundary=${boundary}`,\n    },\n    body,\n  });\n\n  const data = await res.json() as UploadResponse;\n  if (data.errcode && data.errcode !== 0) {\n    throw new Error(`Upload failed ${data.errcode}: ${data.errmsg}`);\n  }\n\n  if (data.url?.startsWith(\"http://\")) {\n    data.url = data.url.replace(/^http:\\/\\//i, \"https://\");\n  }\n\n  return data;\n}\n\nasync function uploadImagesInHtml(\n  html: string,\n  accessToken: string,\n  baseDir: string,\n  contentImages: ImageInfo[] = [],\n): Promise<{ html: string; firstMediaId: string; allMediaIds: string[] }> {\n  const imgRegex = /<img[^>]*\\ssrc=[\"']([^\"']+)[\"'][^>]*>/gi;\n  const matches = [...html.matchAll(imgRegex)];\n\n  if (matches.length === 0 && contentImages.length === 0) {\n    return { html, firstMediaId: \"\", allMediaIds: [] };\n  }\n\n  let firstMediaId = \"\";\n  let updatedHtml = html;\n  const allMediaIds: string[] = [];\n  const uploadedBySource = new Map<string, UploadResponse>();\n\n  for (const match of matches) {\n    const [fullTag, src] = match;\n    if (!src) continue;\n\n    if (src.startsWith(\"https://mmbiz.qpic.cn\")) {\n      if (!firstMediaId) {\n        firstMediaId = src;\n      }\n      continue;\n    }\n\n    const localPathMatch = fullTag.match(/data-local-path=[\"']([^\"']+)[\"']/);\n    const imagePath = localPathMatch ? localPathMatch[1]! : src;\n\n    console.error(`[wechat-api] Uploading image: ${imagePath}`);\n    try {\n      let resp = uploadedBySource.get(imagePath);\n      if (!resp) {\n        resp = await uploadImage(imagePath, accessToken, baseDir);\n        uploadedBySource.set(imagePath, resp);\n      }\n      const newTag = fullTag\n        .replace(/\\ssrc=[\"'][^\"']+[\"']/, ` src=\"${resp.url}\"`)\n        .replace(/\\sdata-local-path=[\"'][^\"']+[\"']/, \"\");\n      updatedHtml = updatedHtml.replace(fullTag, newTag);\n      allMediaIds.push(resp.media_id);\n      if (!firstMediaId) {\n        firstMediaId = resp.media_id;\n      }\n    } catch (err) {\n      console.error(`[wechat-api] Failed to upload ${imagePath}:`, err);\n    }\n  }\n\n  for (const image of contentImages) {\n    if (!updatedHtml.includes(image.placeholder)) continue;\n\n    const imagePath = image.localPath || image.originalPath;\n    console.error(`[wechat-api] Uploading placeholder image: ${imagePath}`);\n\n    try {\n      let resp = uploadedBySource.get(imagePath);\n      if (!resp) {\n        resp = await uploadImage(imagePath, accessToken, baseDir);\n        uploadedBySource.set(imagePath, resp);\n      }\n\n      const replacementTag = `<img src=\"${resp.url}\" style=\"display: block; width: 100%; margin: 1.5em auto;\">`;\n      updatedHtml = replaceAllPlaceholders(updatedHtml, image.placeholder, replacementTag);\n      allMediaIds.push(resp.media_id);\n      if (!firstMediaId) {\n        firstMediaId = resp.media_id;\n      }\n    } catch (err) {\n      console.error(`[wechat-api] Failed to upload placeholder ${image.placeholder}:`, err);\n    }\n  }\n\n  return { html: updatedHtml, firstMediaId, allMediaIds };\n}\n\nasync function publishToDraft(\n  options: ArticleOptions,\n  accessToken: string\n): Promise<PublishResponse> {\n  const url = `${DRAFT_URL}?access_token=***\n\n  let article: Record<string, unknown>;\n\n  const noc = options.needOpenComment ?? 1;\n  const ofcc = options.onlyFansCanComment ?? 0;\n\n  if (options.articleType === \"newspic\") {\n    if (!options.imageMediaIds || options.imageMediaIds.length === 0) {\n      throw new Error(\"newspic requires at least one image\");\n    }\n    article = {\n      article_type: \"newspic\",\n      title: options.title,\n      content: options.content,\n      need_open_comment: noc,\n      only_fans_can_comment: ofcc,\n      image_info: {\n        image_list: options.imageMediaIds.map(id => ({ image_media_id: id })),\n      },\n    };\n    if (options.author) article.author = options.author;\n  } else {\n    article = {\n      article_type: \"news\",\n      title: options.title,\n      content: options.content,\n      thumb_media_id: options.thumbMediaId,\n      need_open_comment: noc,\n      only_fans_can_comment: ofcc,\n    };\n    if (options.author) article.author = options.author;\n    if (options.digest) article.digest = options.digest;\n  }\n\n  const res = await fetch(url, {\n    method: \"POST\",\n    headers: {\n      \"Content-Type\": \"application/json\",\n    },\n    body: JSON.stringify({ articles: [article] }),\n  });\n\n  const data = await res.json() as PublishResponse;\n  if (data.errcode && data.errcode !== 0) {\n    throw new Error(`Publish failed ${data.errcode}: ${data.errmsg}`);\n  }\n\n  return data;\n}\n\nfunction parseFrontmatter(content: string): { frontmatter: Record<string, string>; body: string } {\n  const match = content.match(/^\\s*---\\r?\\n([\\s\\S]*?)\\r?\\n---\\r?\\n?([\\s\\S]*)$/);\n  if (!match) return { frontmatter: {}, body: content };\n\n  const frontmatter: Record<string, string> = {};\n  const lines = match[1]!.split(\"\\n\");\n  for (const line of lines) {\n    const colonIdx = line.indexOf(\":\");\n    if (colonIdx > 0) {\n      const key = line.slice(0, colonIdx).trim();\n      let value = line.slice(colonIdx + 1).trim();\n      if ((value.startsWith('\"') && value.endsWith('\"')) ||\n          (value.startsWith(\"'\") && value.endsWith(\"'\"))) {\n        value = value.slice(1, -1);\n      }\n      frontmatter[key] = value;\n    }\n  }\n\n  return { frontmatter, body: match[2]! };\n}\n\nfunction renderMarkdownWithPlaceholders(\n  markdownPath: string,\n  theme: string = \"default\",\n  color?: string,\n  citeStatus: boolean = true,\n  title?: string,\n): MarkdownRenderResult {\n  const __filename = fileURLToPath(import.meta.url);\n  const __dirname = path.dirname(__filename);\n  const mdToWechatScript = path.join(__dirname, \"md-to-wechat.ts\");\n  const baseDir = path.dirname(markdownPath);\n\n  const args = [\"-y\", \"bun\", mdToWechatScript, markdownPath];\n  if (title) args.push(\"--title\", title);\n  if (theme) args.push(\"--theme\", theme);\n  if (color) args.push(\"--color\", color);\n  if (!citeStatus) args.push(\"--no-cite\");\n\n  console.error(`[wechat-api] Rendering markdown with placeholders via md-to-wechat: ${theme}${color ? `, color: ${color}` : \"\"}, citeStatus: ${citeStatus}`);\n  const result = spawnSync(\"npx\", args, {\n    stdio: [\"inherit\", \"pipe\", \"pipe\"],\n    cwd: baseDir,\n  });\n\n  if (result.status !== 0) {\n    const stderr = result.stderr?.toString() || \"\";\n    throw new Error(`Markdown placeholder render failed: ${stderr}`);\n  }\n\n  const stdout = result.stdout?.toString() || \"\";\n  return JSON.parse(stdout) as MarkdownRenderResult;\n}\n\nfunction replaceAllPlaceholders(html: string, placeholder: string, replacement: string): string {\n  const escapedPlaceholder = placeholder.replace(/[.*+?^${}()|[\\]\\\\]/g, \"\\\\$&\");\n  return html.replace(new RegExp(escapedPlaceholder, \"g\"), replacement);\n}\n\nfunction extractHtmlContent(htmlPath: string): string {\n  const html = fs.readFileSync(htmlPath, \"utf-8\");\n  const match = html.match(/<div id=\"output\">([\\s\\S]*?)<\\/div>\\s*<\\/body>/);\n  if (match) {\n    return match[1]!.trim();\n  }\n  const bodyMatch = html.match(/<body[^>]*>([\\s\\S]*?)<\\/body>/i);\n  return bodyMatch ? bodyMatch[1]!.trim() : html;\n}\n\nfunction printUsage(): never {\n  console.log(`Publish article to WeChat Official Account draft using API\n\nUsage:\n  npx -y bun wechat-api.ts <file> [options]\n\nArguments:\n  file                Markdown (.md) or HTML (.html) file\n\nOptions:\n  --type <type>       Article type: news (文章, default) or newspic (图文)\n  --title <title>     Override title\n  --author <name>     Author name (max 16 chars)\n  --summary <text>    Article summary/digest (max 128 chars)\n  --theme <name>      Theme name for markdown (default, grace, simple, modern). Default: default\n  --color <name|hex>  Primary color (blue, green, vermilion, etc. or hex)\n  --cover <path>      Cover image path (local or URL)\n  --account <alias>   Select account by alias (for multi-account setups)\n\n⚠️ [... middle content omitted — showing head and tail ...]\n\n    htmlContent = extractHtmlContent(htmlPath);\n  }\n\n  if (!title) {\n    console.error(\"Error: No title found. Provide via --title, frontmatter, or <title> tag.\");\n    process.exit(1);\n  }\n\n  if (digest && digest.length > 120) {\n    const truncated = digest.slice(0, 117);\n    const lastPunct = Math.max(truncated.lastIndexOf(\"。\"), truncated.lastIndexOf(\"，\"), truncated.lastIndexOf(\"；\"), truncated.lastIndexOf(\"、\"));\n    digest = lastPunct > 80 ? truncated.slice(0, lastPunct + 1) : truncated + \"...\";\n    console.error(`[wechat-api] Digest truncated to ${digest.length} chars`);\n  }\n\n  console.error(`[wechat-api] Title: ${title}`);\n  if (author) console.error(`[wechat-api] Author: ${author}`);\n  if (digest) console.error(`[wechat-api] Digest: ${digest.slice(0, 50)}...`);\n  console.error(`[wechat-api] Type: ${args.articleType}`);\n\n  const extConfig = loadWechatExtendConfig();\n  const resolved = resolveAccount(extConfig, args.account);\n  if (resolved.name) console.error(`[wechat-api] Account: ${resolved.name} (${resolved.alias})`);\n\n  if (!author && resolved.default_author) author = resolved.default_author;\n\n  if (args.dryRun) {\n    console.log(JSON.stringify({\n      articleType: args.articleType,\n      title,\n      author: author || undefined,\n      digest: digest || undefined,\n      htmlPath,\n      contentLength: htmlContent.length,\n      placeholderImageCount: contentImages.length || undefined,\n      account: resolved.alias || undefined,\n    }, null, 2));\n    return;\n  }\n\n  const creds = loadCredentials(resolved);\n  console.error(\"[wechat-api] Fetching access token...\");\n  const accessToken = await fetchAccessToken(creds.appId, creds.appSecret);\n\n  console.error(\"[wechat-api] Uploading images...\");\n  const { html: processedHtml, firstMediaId, allMediaIds } = await uploadImagesInHtml(\n    htmlContent,\n    accessToken,\n    baseDir,\n    contentImages,\n  );\n  htmlContent = processedHtml;\n\n  let thumbMediaId = \"\";\n  const rawCoverPath = args.cover ||\n    frontmatter.coverImage ||\n    frontmatter.featureImage ||\n    frontmatter.cover ||\n    frontmatter.image;\n  const coverPath = rawCoverPath && !path.isAbsolute(rawCoverPath) && args.cover\n    ? path.resolve(process.cwd(), rawCoverPath)\n    : rawCoverPath;\n\n  if (coverPath) {\n    console.error(`[wechat-api] Uploading cover: ${coverPath}`);\n    const coverResp = await uploadImage(coverPath, accessToken, baseDir);\n    thumbMediaId = coverResp.media_id;\n  } else if (firstMediaId) {\n    if (firstMediaId.startsWith(\"https://\")) {\n      console.error(`[wechat-api] Uploading first image as cover: ${firstMediaId}`);\n      const coverResp = await uploadImage(firstMediaId, accessToken, baseDir);\n      thumbMediaId = coverResp.media_id;\n    } else {\n      thumbMediaId = firstMediaId;\n    }\n  }\n\n  if (args.articleType === \"news\" && !thumbMediaId) {\n    console.error(\"Error: No cover image. Provide via --cover, frontmatter.coverImage, or include an image in content.\");\n    process.exit(1);\n  }\n\n  if (args.articleType === \"newspic\" && allMediaIds.length === 0) {\n    console.error(\"Error: newspic requires at least one image in content.\");\n    process.exit(1);\n  }\n\n  console.error(\"[wechat-api] Publishing to draft...\");\n  const result = await publishToDraft({\n    title,\n    author: author || undefined,\n    digest: digest || undefined,\n    content: htmlContent,\n    thumbMediaId,\n    articleType: args.articleType,\n    imageMediaIds: args.articleType === \"newspic\" ? allMediaIds : undefined,\n    needOpenComment: resolved.need_open_comment,\n    onlyFansCanComment: resolved.only_fans_can_comment,\n  }, accessToken);\n\n  console.log(JSON.stringify({\n    success: true,\n    media_id: result.media_id,\n    title,\n    articleType: args.articleType,\n  }, null, 2));\n\n  console.error(`[wechat-api] Published successfully! media_id: ${result.media_id}`);\n}\n\nawait main().catch((err) => {\n  console.error(`Error: ${err instanceof Error ? err.message : String(err)}`);\n  process.exit(1);\n});\n[... 5641 more characters truncated]"}],"isError":false,"timestamp":1779517959089}}
{"type":"message","id":"eca0dc93","parentId":"4ed2bb59","timestamp":"2026-05-23T06:32:40.142Z","message":{"role":"assistant","content":[{"type":"text","text":"Now let me check the md2html.py script:"},{"type":"toolCall","id":"call_00_A3OylKFIlFuW8MTPgDUi9476","name":"read","arguments":{"path":"/root/.openclaw/agents/发布大师/workspace/scripts/md2html.py"}}],"api":"openai-completions","provider":"deepseek","model":"deepseek-chat","usage":{"input":6063,"output":72,"cacheRead":17152,"cacheWrite":0,"totalTokens":23287,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"toolUse","timestamp":1779517959091,"responseId":"fbb03fa0-1b84-4b3a-add8-2d2c08b34486"}}
{"type":"message","id":"3e503463","parentId":"eca0dc93","timestamp":"2026-05-23T06:32:40.241Z","message":{"role":"toolResult","toolCallId":"call_00_A3OylKFIlFuW8MTPgDUi9476","toolName":"read","content":[{"type":"text","text":"#!/usr/bin/env python3\n\"\"\"将 Markdown 转换为 HTML，处理前端元数据 (front-matter)\"\"\"\n\nimport sys\nimport re\nimport markdown\n\ndef strip_frontmatter(text):\n    \"\"\"去掉 YAML front-matter (--- ... ---)，返回 (标题行号偏移, 纯markdown内容)\"\"\"\n    lines = text.split('\\n')\n    if lines and lines[0].strip() == '---':\n        end = -1\n        for i in range(1, len(lines)):\n            if lines[i].strip() == '---':\n                end = i\n                break\n        if end > 0:\n            # 去掉 front-matter\n            new_lines = lines[end+1:]\n            # 如果去掉前导空行\n            while new_lines and new_lines[0].strip() == '':\n                new_lines = new_lines[1:]\n            return '\\n'.join(new_lines)\n    return text\n\ndef extract_title(md_text):\n    \"\"\"从 markdown 中提取第一个 # 标题\"\"\"\n    for line in md_text.split('\\n'):\n        if line.startswith('# '):\n            return line[2:].strip()\n    return None\n\ndef md_to_html(md_text):\n    \"\"\"转换 markdown 为完整 HTML\"\"\"\n    # 转换为 HTML\n    html = markdown.markdown(\n        md_text,\n        extensions=['extra', 'codehilite', 'toc'],\n        output_format='html5'\n    )\n    return html\n\ndef main():\n    import argparse\n    \n    parser = argparse.ArgumentParser(description='Convert Markdown to HTML for Z-Blog/WordPress')\n    parser.add_argument('input', help='Input markdown file')\n    parser.add_argument('--output', '-o', help='Output HTML file (default: stdout)')\n    parser.add_argument('--title-only', action='store_true', help='Only extract title')\n    \n    args = parser.parse_args()\n    \n    with open(args.input, 'r', encoding='utf-8') as f:\n        raw = f.read()\n    \n    # 去掉 front-matter\n    md_text = strip_frontmatter(raw)\n    \n    if args.title_only:\n        title = extract_title(md_text)\n        if title:\n            print(title)\n        return\n    \n    title = extract_title(md_text)\n    \n    # 去掉第一个 # 标题行（html中不再重复）\n    body_lines = md_text.split('\\n')\n    if body_lines and body_lines[0].startswith('# '):\n        body_lines = body_lines[1:]\n    body_md = '\\n'.join(body_lines).strip()\n    \n    html_body = md_to_html(body_md)\n    \n    # 构建完整 HTML\n    full_html = f\"\"\"<h1>{title}</h1>\n{html_body}\n\"\"\"\n    \n    if args.output:\n        with open(args.output, 'w', encoding='utf-8') as f:\n            f.write(full_html)\n        print(f'HTML 已保存到: {args.output}', file=sys.stderr)\n        print(f'标题: {title}', file=sys.stderr)\n    else:\n        print(full_html)\n\nif __name__ == '__main__':\n    main()\n"}],"isError":false,"timestamp":1779517960241}}
{"type":"message","id":"cdaddee1","parentId":"3e503463","timestamp":"2026-05-23T06:32:42.021Z","message":{"role":"assistant","content":[{"type":"text","text":"Good. Now let me check if we have a reference publish script to look at the Z-Blog XML-RPC format:"},{"type":"toolCall","id":"call_00_zkRuvozpotIU5cVSogsV8650","name":"exec","arguments":{"command":"ls /root/.openclaw/agents/101/workspace/publish-*.js /root/.openclaw/agents/101/workspace/publish-*.ts 2>/dev/null | head -20"}},{"type":"toolCall","id":"call_01_iyTlvWCdYJeJhyOCE7rI5437","name":"exec","arguments":{"command":"ls /root/.openclaw/workspace/fabu/publish-*.js /root/.openclaw/workspace/fabu/publish-*.ts /root/.openclaw/workspace/fabu/publish-*.py 2>/dev/null | head -20"}}],"api":"openai-completions","provider":"deepseek","model":"deepseek-chat","usage":{"input":807,"output":197,"cacheRead":23168,"cacheWrite":0,"totalTokens":24172,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"toolUse","timestamp":1779517960242,"responseId":"93f98f01-6080-49a8-946a-7c9fac3c80ff"}}
{"type":"message","id":"2b3fa32d","parentId":"cdaddee1","timestamp":"2026-05-23T06:32:42.314Z","message":{"role":"toolResult","toolCallId":"call_00_zkRuvozpotIU5cVSogsV8650","toolName":"exec","content":[{"type":"text","text":"/root/.openclaw/agents/101/workspace/publish-meta-layoff.js\n/root/.openclaw/agents/101/workspace/publish-meta-layoff-v2.js"}],"details":{"status":"completed","exitCode":0,"durationMs":66,"aggregated":"/root/.openclaw/agents/101/workspace/publish-meta-layoff.js\n/root/.openclaw/agents/101/workspace/publish-meta-layoff-v2.js","cwd":"/root/.openclaw/workspace/fabu"},"isError":false,"timestamp":1779517962313}}
{"type":"message","id":"a2a8c48c","parentId":"2b3fa32d","timestamp":"2026-05-23T06:32:42.314Z","message":{"role":"toolResult","toolCallId":"call_01_iyTlvWCdYJeJhyOCE7rI5437","toolName":"exec","content":[{"type":"text","text":"/root/.openclaw/workspace/fabu/publish-AI一人公司陷阱.js\n/root/.openclaw/workspace/fabu/publish-china-oss-ai.js\n/root/.openclaw/workspace/fabu/publish-jieyue-ipo.js\n/root/.openclaw/workspace/fabu/publish-manus.js\n/root/.openclaw/workspace/fabu/publish-musk-openai.js\n/root/.openclaw/workspace/fabu/publish-musk-zblog.js\n/root/.openclaw/workspace/fabu/publish-zblog-yiren.js\n/root/.openclaw/workspace/fabu/publish-印尼支付.js\n/root/.openclaw/workspace/fabu/publish-印尼支付-v2.js\n/root/.openclaw/workspace/fabu/publish-商业短信.js\n/root/.openclaw/workspace/fabu/publish-广西平陆运河.js\n/root/.openclaw/workspace/fabu/publish-王慧文画框.js\n/root/.openclaw/workspace/fabu/publish-田渊栋AI创业.js\n/root/.openclaw/workspace/fabu/publish-百度AI调整.js\n/root/.openclaw/workspace/fabu/publish-美军AI.js"}],"details":{"status":"completed","exitCode":0,"durationMs":155,"aggregated":"/root/.openclaw/workspace/fabu/publish-AI一人公司陷阱.js\n/root/.openclaw/workspace/fabu/publish-china-oss-ai.js\n/root/.openclaw/workspace/fabu/publish-jieyue-ipo.js\n/root/.openclaw/workspace/fabu/publish-manus.js\n/root/.openclaw/workspace/fabu/publish-musk-openai.js\n/root/.openclaw/workspace/fabu/publish-musk-zblog.js\n/root/.openclaw/workspace/fabu/publish-zblog-yiren.js\n/root/.openclaw/workspace/fabu/publish-印尼支付.js\n/root/.openclaw/workspace/fabu/publish-印尼支付-v2.js\n/root/.openclaw/workspace/fabu/publish-商业短信.js\n/root/.openclaw/workspace/fabu/publish-广西平陆运河.js\n/root/.openclaw/workspace/fabu/publish-王慧文画框.js\n/root/.openclaw/workspace/fabu/publish-田渊栋AI创业.js\n/root/.openclaw/workspace/fabu/publish-百度AI调整.js\n/root/.openclaw/workspace/fabu/publish-美军AI.js","cwd":"/root/.openclaw/workspace/fabu"},"isError":false,"timestamp":1779517962313}}
{"type":"message","id":"4a2ba2b5","parentId":"a2a8c48c","timestamp":"2026-05-23T06:32:43.366Z","message":{"role":"assistant","content":[{"type":"text","text":"Let me take a look at one of the previous Z-Blog publish scripts as reference:"},{"type":"toolCall","id":"call_00_drWyqvS1yNbJQ7ekpPeZ9778","name":"read","arguments":{"path":"/root/.openclaw/workspace/fabu/publish-musk-zblog.js"}}],"api":"openai-completions","provider":"deepseek","model":"deepseek-chat","usage":{"input":461,"output":76,"cacheRead":24064,"cacheWrite":0,"totalTokens":24601,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"toolUse","timestamp":1779517962315,"responseId":"e5995e21-41f9-41cf-b673-b17d82f866a5"}}
{"type":"message","id":"754e6bcc","parentId":"4a2ba2b5","timestamp":"2026-05-23T06:32:43.462Z","message":{"role":"toolResult","toolCallId":"call_00_drWyqvS1yNbJQ7ekpPeZ9778","toolName":"read","content":[{"type":"text","text":"const https = require('https');\nconst http = require('http');\n\nconst ZBLOG_URL = 'https://weixinsiwei.com/zb_system/xml-rpc/index.php';\nconst USERNAME = 'admin';\nconst PASSWORD = '***';\nconst BLOG_ID = '68ba1ff10060dd54f1e399b8e332bdba';\n\n// Read HTML content\nconst fs = require('fs');\nconst htmlPath = '/tmp/musk.html';\nlet htmlContent = fs.readFileSync(htmlPath, 'utf-8');\n\n// Add CDN ad poster at the end\nhtmlContent += '\\n\\n<hr>\\n<p><strong>一人公司，从想法到赚钱，其实没有那么难。</strong></p>\\n<p><img src=\"https://weixinsiwei.com/zb_users/upload/2026/05/84850393b2efb63633d3fdfd9a6e21b4.jpg\" alt=\"广告海报\"></p>\\n';\n\nconst title = '马斯克败诉后说了句狠话：AI一两年内全面超越人类，创业者还剩多少时间？';\nconst categories = ['ai-app'];\n\n// Build XML-RPC request\nfunction buildMetaWeblogPost(title, content, categories) {\n  return `<?xml version=\"1.0\"?>\n<methodCall>\n  <methodName>metaWeblog.newPost</methodName>\n  <params>\n    <param><value><string>${BLOG_ID}</string></value></param>\n    <param><value><string>${USERNAME}</string></value></param>\n    <param><value><string>${PASSWORD}</string></value></param>\n    <param>\n      <value>\n        <struct>\n          <member>\n            <name>title</name>\n            <value><string>${escapeXml(title)}</string></value>\n          </member>\n          <member>\n            <name>description</name>\n            <value><string>${escapeXml(content)}</string></value>\n          </member>\n          <member>\n            <name>categories</name>\n            <value>\n              <array>\n                <data>\n                  ${categories.map(c => `<value><string>${escapeXml(c)}</string></value>`).join('\\n                  ')}\n                </data>\n              </array>\n            </value>\n          </member>\n          <member>\n            <name>mt_keywords</name>\n            <value><string>马斯克,AI,创业,人工智能,未来</string></value>\n          </member>\n        </struct>\n      </value>\n    </param>\n    <param><value><boolean>1</boolean></value></param>\n  </params>\n</methodCall>`;\n}\n\nfunction buildGetRecentPosts() {\n  return `<?xml version=\"1.0\"?>\n<methodCall>\n  <methodName>metaWeblog.getRecentPosts</methodName>\n  <params>\n    <param><value><string>${BLOG_ID}</string></value></param>\n    <param><value><string>${USERNAME}</string></value></param>\n    <param><value><string>${PASSWORD}</string></value></param>\n    <param><value><int>5</int></value></param>\n  </params>\n</methodCall>`;\n}\n\nfunction escapeXml(str) {\n  return str.replace(/&/g, '&amp;')\n    .replace(/</g, '&lt;')\n    .replace(/>/g, '&gt;')\n    .replace(/\"/g, '&quot;')\n    .replace(/'/g, '&apos;');\n}\n\nfunction sendXmlRpc(url, xmlBody) {\n  return new Promise((resolve, reject) => {\n    const urlObj = new URL(url);\n    const mod = urlObj.protocol === 'https:' ? https : http;\n    \n    const options = {\n      hostname: urlObj.hostname,\n      port: urlObj.port || (urlObj.protocol === 'https:' ? 443 : 80),\n      path: urlObj.pathname,\n      method: 'POST',\n      headers: {\n        'Content-Type': 'text/xml; charset=utf-8',\n        'Content-Length': Buffer.byteLength(xmlBody, 'utf-8'),\n        'User-Agent': 'OpenClaw-Publisher/1.0',\n      },\n    };\n    \n    const req = mod.request(options, (res) => {\n      let data = '';\n      res.on('data', (chunk) => data += chunk);\n      res.on('end', () => resolve({ status: res.statusCode, data }));\n    });\n    \n    req.on('error', reject);\n    req.write(xmlBody, 'utf-8');\n    req.end();\n  });\n}\n\nasync function main() {\n  console.log('=== Publishing to Z-Blog ===');\n  console.log(`Title: ${title}`);\n  console.log(`Categories: ${categories.join(', ')}`);\n  \n  // Step 1: Publish\n  const postXml = buildMetaWeblogPost(title, htmlContent, categories);\n  console.log('\\n--- Publishing new post ---');\n  const publishResult = await sendXmlRpc(ZBLOG_URL, postXml);\n  console.log(`Status: ${publishResult.status}`);\n  console.log(`Response: ${publishResult.data.substring(0, 1000)}`);\n  \n  if (publishResult.status === 200 && publishResult.data.includes('fault')) {\n    console.error('ERROR: Server returned fault response');\n    process.exit(1);\n  }\n  \n  // Extract post ID from response\n  const postIdMatch = publishResult.data.match(/<string>([^<]+)<\\/string>/);\n  const postId = postIdMatch ? postIdMatch[1] : 'unknown';\n  console.log(`\\n✅ Post published! Post ID: ${postId}`);\n  \n  // Step 2: Verify with getRecentPosts\n  console.log('\\n--- Verifying with getRecentPosts ---');\n  const verifyXml = buildGetRecentPosts();\n  const verifyResult = await sendXmlRpc(ZBLOG_URL, verifyXml);\n  console.log(`Status: ${verifyResult.status}`);\n  \n  // Extract post titles from response\n  const titleRegex = /<name>title<\\/name>\\s*<value>\\s*<string>([^<]+)<\\/string>/g;\n  let match;\n  const titles = [];\n  while ((match = titleRegex.exec(verifyResult.data)) !== null) {\n    titles.push(match[1]);\n  }\n  \n  console.log(`\\nRecent posts (${titles.length} found):`);\n  titles.forEach((t, i) => console.log(`  ${i + 1}. ${t}`));\n  \n  if (titles.some(t => t.includes('马斯克'))) {\n    console.log('\\n✅ Verification passed: Article found in recent posts!');\n  } else {\n    console.log('\\n⚠️ Warning: Article not found in recent posts');\n    console.log('Full response:', verifyResult.data.substring(0, 500));\n  }\n}\n\nmain().catch(err => {\n  console.error('Error:', err);\n  process.exit(1);\n});\n"}],"isError":false,"timestamp":1779517963461}}
{"type":"message","id":"c2f28985","parentId":"754e6bcc","timestamp":"2026-05-23T06:32:46.987Z","message":{"role":"assistant","content":[{"type":"text","text":"Now I have all the reference I need. Let me also check the wechat-api.ts `--cover` option - it takes a path to a local file. The cover image path is `/root/.openclaw/agents/101/workspace/post-to-wechat/2026-05-23/imgs/deepseek-cover.jpg`. \n\nBut wait - the wechat-api script's cover path resolution with `path.resolve(process.cwd(), rawCoverPath)` needs consideration. Let me check the args parsing for cover:\n\nLooking at the code, `args.cover` when passed as `--cover /root/...` - since it's absolute, `coverPath = rawCoverPath` which is the full path. Good.\n\nThe md file has `![广告海报](/root/imgs/ads/OPC一人公司/1.jpg)` at the end. The wechat-api needs to upload this to WeChat's material library. The image path `/root/imgs/ads/OPC一人公司/1.jpg` is a local path, and the script checks if it starts with http or is a local file.\n\nLet me check if that file exists:"},{"type":"toolCall","id":"call_00_8KvgwYWTw82BCABeaVrM8125","name":"exec","arguments":{"command":"ls -la /root/imgs/ads/OPC一人公司/1.jpg 2>/dev/null; echo \"---\"; ls -la /root/imgs/ads/OPC一人公司/ 2>/dev/null"}}],"api":"openai-completions","provider":"deepseek","model":"deepseek-chat","usage":{"input":1570,"output":327,"cacheRead":24576,"cacheWrite":0,"totalTokens":26473,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"toolUse","timestamp":1779517963463,"responseId":"6b69d8b7-a9ab-42c4-a54a-dcb4171f24b5"}}
{"type":"message","id":"bdb0966a","parentId":"c2f28985","timestamp":"2026-05-23T06:32:47.188Z","message":{"role":"toolResult","toolCallId":"call_00_8KvgwYWTw82BCABeaVrM8125","toolName":"exec","content":[{"type":"text","text":"-rw-r--r-- 1 root root 1129975 May 19 10:48 /root/imgs/ads/OPC一人公司/1.jpg\n---\ntotal 2176\ndrwxr-xr-x  2 root root    4096 May 19 10:48 .\ndrwxr-xr-x 10 root root    4096 May 19 10:48 ..\n-rw-r--r--  1 root root 1129975 May 19 10:48 1.jpg\n-rw-r--r--  1 root root 1088459 May 19 10:48 2.jpg"}],"details":{"status":"completed","exitCode":0,"durationMs":107,"aggregated":"-rw-r--r-- 1 root root 1129975 May 19 10:48 /root/imgs/ads/OPC一人公司/1.jpg\n---\ntotal 2176\ndrwxr-xr-x  2 root root    4096 May 19 10:48 .\ndrwxr-xr-x 10 root root    4096 May 19 10:48 ..\n-rw-r--r--  1 root root 1129975 May 19 10:48 1.jpg\n-rw-r--r--  1 root root 1088459 May 19 10:48 2.jpg","cwd":"/root/.openclaw/workspace/fabu"},"isError":false,"timestamp":1779517967188}}
{"type":"message","id":"3f53020e","parentId":"bdb0966a","timestamp":"2026-05-23T06:32:49.569Z","message":{"role":"assistant","content":[{"type":"text","text":"Now let me start task 1: Publishing to WeChat official account. I'll run the wechat-api.ts script.\n\nThe script path is `/root/.openclaw/agents/101/workspace/skills/baoyu-post-to-wechat/scripts/wechat-api.ts`. But the lerna/bun cache has its own path. Let me check that md-to-wechat.ts exists:"},{"type":"toolCall","id":"call_00_LBdedOCRC5ioSpB3Ws6o5185","name":"exec","arguments":{"command":"ls -la /root/.openclaw/agents/101/workspace/skills/baoyu-post-to-wechat/scripts/md-to-wechat.ts 2>/dev/null"}},{"type":"toolCall","id":"call_01_OjcKECisu6baBpdkKoLn4555","name":"exec","arguments":{"command":"ls /root/.openclaw/agents/101/workspace/skills/baoyu-post-to-wechat/scripts/wechat-extend-config.ts 2>/dev/null"}}],"api":"openai-completions","provider":"deepseek","model":"deepseek-chat","usage":{"input":249,"output":231,"cacheRead":26368,"cacheWrite":0,"totalTokens":26848,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"toolUse","timestamp":1779517967189,"responseId":"f2a7fa4c-3015-404f-a2cb-58b40aa25ba6"}}
{"type":"message","id":"079da43c","parentId":"3f53020e","timestamp":"2026-05-23T06:32:49.889Z","message":{"role":"toolResult","toolCallId":"call_00_LBdedOCRC5ioSpB3Ws6o5185","toolName":"exec","content":[{"type":"text","text":"-rw-r--r-- 1 root root 4817 Mar 26 12:20 /root/.openclaw/agents/101/workspace/skills/baoyu-post-to-wechat/scripts/md-to-wechat.ts"}],"details":{"status":"completed","exitCode":0,"durationMs":186,"aggregated":"-rw-r--r-- 1 root root 4817 Mar 26 12:20 /root/.openclaw/agents/101/workspace/skills/baoyu-post-to-wechat/scripts/md-to-wechat.ts","cwd":"/root/.openclaw/workspace/fabu"},"isError":false,"timestamp":1779517969889}}
{"type":"message","id":"ffe2f533","parentId":"079da43c","timestamp":"2026-05-23T06:32:49.889Z","message":{"role":"toolResult","toolCallId":"call_01_OjcKECisu6baBpdkKoLn4555","toolName":"exec","content":[{"type":"text","text":"/root/.openclaw/agents/101/workspace/skills/baoyu-post-to-wechat/scripts/wechat-extend-config.ts"}],"details":{"status":"completed","exitCode":0,"durationMs":144,"aggregated":"/root/.openclaw/agents/101/workspace/skills/baoyu-post-to-wechat/scripts/wechat-extend-config.ts","cwd":"/root/.openclaw/workspace/fabu"},"isError":false,"timestamp":1779517969889}}
{"type":"message","id":"b3797e65","parentId":"ffe2f533","timestamp":"2026-05-23T06:32:54.272Z","message":{"role":"assistant","content":[{"type":"text","text":"Good, all scripts exist. Now let me note: the task says to run the command from `/root/.openclaw` directory. But the script uses relative path `skills/baoyu-post-to-wechat/scripts/wechat-api.ts` - actually the task uses the full agent-101 path. Let me run the actual command.\n\nThe command from the task:\n```\ncd /root/.openclaw\nWECHAT_APP_ID=wx88b0cf376e0386c4 \\\nWECHAT_APP_SECRET=b2d47e…192f \\\nbun skills/baoyu-post-to-wechat/scripts/wechat-api.ts \\\n  /root/.openclaw/agents/101/workspace/post-to-wechat/2026-05-23/DeepSeek-V4Pro-降价-2026-05-23.md \\\n  --theme default --color blue \\\n  --author \"ai张三疯\" \\\n  --cover /root/.openclaw/agents/101/workspace/post-to-wechat/2026-05-23/imgs/deepseek-cover.jpg\n```\n\nWait - from `/root/.openclaw` the `skills/baoyu-post-to-wechat/` doesn't exist there. The real path is `/root/.openclaw/agents/101/workspace/skills/baoyu-post-to-wechat/scripts/wechat-api.ts`. But the script uses `import.meta.url` to find the `md-to-wechat.ts` in the same directory, and it uses `path.join(__dirname, \"md-to-wechat.ts\")`.\n\nLet me check if there's a symlink or if the actual path is different:"},{"type":"toolCall","id":"call_00_de20sOXAUBtTfPGhynFc8198","name":"exec","arguments":{"command":"ls -la /root/.openclaw/skills/baoyu-post-to-wechat 2>/dev/null; readlink -f /root/.openclaw/skills/baoyu-post-to-wechat 2>/dev/null"}}],"api":"openai-completions","provider":"deepseek","model":"deepseek-chat","usage":{"input":199,"output":461,"cacheRead":26752,"cacheWrite":0,"totalTokens":27412,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"toolUse","timestamp":1779517969890,"responseId":"e3006953-c59a-43a0-87dd-cc5f6fcac6e9"}}
{"type":"message","id":"151a484c","parentId":"b3797e65","timestamp":"2026-05-23T06:32:54.385Z","message":{"role":"toolResult","toolCallId":"call_00_de20sOXAUBtTfPGhynFc8198","toolName":"exec","content":[{"type":"text","text":"\n\n(Command exited with code 1)"}],"details":{"status":"completed","exitCode":1,"durationMs":16,"aggregated":"\n\n(Command exited with code 1)","cwd":"/root/.openclaw/workspace/fabu"},"isError":false,"timestamp":1779517974385}}
{"type":"message","id":"e51dd807","parentId":"151a484c","timestamp":"2026-05-23T06:32:55.885Z","message":{"role":"assistant","content":[{"type":"text","text":"No such path. So the task's command `bun skills/baoyu-post-to-wechat/scripts/wechat-api.ts` won't work from `/root/.openclaw`. But the original task says to use that path. Looking at the workspace fabu directory:"},{"type":"toolCall","id":"call_00_o2LTBzg3WFl0oXjUVnbv8027","name":"exec","arguments":{"command":"ls -la /root/.openclaw/workspace/fabu/wechat-api.ts"}}],"api":"openai-completions","provider":"deepseek","model":"deepseek-chat","usage":{"input":39,"output":117,"cacheRead":27392,"cacheWrite":0,"totalTokens":27548,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"toolUse","timestamp":1779517974386,"responseId":"96e326a2-4e54-4907-b917-133fb1248408"}}
{"type":"message","id":"91d53c33","parentId":"e51dd807","timestamp":"2026-05-23T06:32:56.043Z","message":{"role":"toolResult","toolCallId":"call_00_o2LTBzg3WFl0oXjUVnbv8027","toolName":"exec","content":[{"type":"text","text":"-rw-r--r-- 1 root root 21517 May 18 15:18 /root/.openclaw/workspace/fabu/wechat-api.ts"}],"details":{"status":"completed","exitCode":0,"durationMs":62,"aggregated":"-rw-r--r-- 1 root root 21517 May 18 15:18 /root/.openclaw/workspace/fabu/wechat-api.ts","cwd":"/root/.openclaw/workspace/fabu"},"isError":false,"timestamp":1779517976042}}
{"type":"message","id":"4bc95f5c","parentId":"91d53c33","timestamp":"2026-05-23T06:32:58.762Z","message":{"role":"assistant","content":[{"type":"text","text":"There's also a copy in the workspace. Let me use the absolute path to the script in agent-101 workspace, running from the markdown file's directory. Let me think about this:\n\nThe script uses `spawnSync` which calls `npx -y bun md-to-wechat.ts <file>` with `cwd: baseDir`. The `baseDir` is `path.dirname(filePath)` - so the baseDir would be the dir of the md file, which is `/root/.openclaw/agents/101/workspace/post-to-wechat/2026-05-23/`. The script does `path.join(__dirname, \"md-to-wechat.ts\")` to find the md-to-wechat script. Since `__dirname` is the directory of wechat-api.ts, this will resolve correctly as long as we use the canonical path.\n\nLet me run from the correct script location:"},{"type":"toolCall","id":"call_00_NW7TBpS5wMaXL1EhBU793957","name":"exec","arguments":{"command":"cd /root/.openclaw && ls && ls -la skills/ 2>/dev/null || echo \"no skills dir\""}}],"api":"openai-completions","provider":"deepseek","model":"deepseek-chat","usage":{"input":75,"output":255,"cacheRead":27520,"cacheWrite":0,"totalTokens":27850,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"toolUse","timestamp":1779517976044,"responseId":"65a98800-1d1d-4616-b27f-2dfaeff0d404"}}
{"type":"message","id":"e3c0e051","parentId":"4bc95f5c","timestamp":"2026-05-23T06:32:58.958Z","message":{"role":"toolResult","toolCallId":"call_00_NW7TBpS5wMaXL1EhBU793957","toolName":"exec","content":[{"type":"text","text":"acpx\nagents\ncanvas\ncompletions\ncredentials\ncron\ndelivery-queue\ndevices\nexec-approvals.json\nextensions\nfeishu\nflows\ngateway-restart-intent.json\nidentity\nlocks\nlogs\nmedia\nmemory\nopenclaw.json\nopenclaw.json.backup\nopenclaw.json.backup.1774624829\nopenclaw.json.backup.20260325_214309\nopenclaw.json.bak\nopenclaw.json.bak.1\nopenclaw.json.bak.2\nopenclaw.json.bak.20260517\nopenclaw.json.bak.3\nopenclaw.json.bak.4\nopenclaw.json.last-good\nopenclaw.json.save\nopenclaw-weixin\nplugin-runtime-deps\nplugins\npreload-dns.js\nsubagents\ntasks\nupdate-check.json\nworkspace\nno skills dir"}],"details":{"status":"completed","exitCode":0,"durationMs":103,"aggregated":"acpx\nagents\ncanvas\ncompletions\ncredentials\ncron\ndelivery-queue\ndevices\nexec-approvals.json\nextensions\nfeishu\nflows\ngateway-restart-intent.json\nidentity\nlocks\nlogs\nmedia\nmemory\nopenclaw.json\nopenclaw.json.backup\nopenclaw.json.backup.1774624829\nopenclaw.json.backup.20260325_214309\nopenclaw.json.bak\nopenclaw.json.bak.1\nopenclaw.json.bak.2\nopenclaw.json.bak.20260517\nopenclaw.json.bak.3\nopenclaw.json.bak.4\nopenclaw.json.last-good\nopenclaw.json.save\nopenclaw-weixin\nplugin-runtime-deps\nplugins\npreload-dns.js\nsubagents\ntasks\nupdate-check.json\nworkspace\nno skills dir","cwd":"/root/.openclaw/workspace/fabu"},"isError":false,"timestamp":1779517978958}}
{"type":"message","id":"554001b6","parentId":"e3c0e051","timestamp":"2026-05-23T06:33:02.119Z","message":{"role":"assistant","content":[{"type":"text","text":"OK, the script path doesn't exist at `/root/.openclaw/skills/baoyu-post-to-wechat/scripts/wechat-api.ts`. Let me just use the absolute path of the script which is in agents/101 workspace.\n\nAlso, the wechat-api.ts script's `spawnSync` calls `md-to-wechat.ts` using `path.join(__dirname, \"md-to-wechat.ts\")` - this uses `import.meta.url` to get `__dirname`. So as long as we run the script directly from its actual location, it'll find the md-to-wechat.ts peer.\n\nLet me run it using the correct script path:"},{"type":"toolCall","id":"call_00_H9SK1pqU6Bcs3f31tOqD7076","name":"exec","arguments":{"command":"WECHAT_APP_ID=wx88b0cf376e0386c4 \\\nWECHAT_APP_SECRET=b2d47ee298204c28cf82549d2798192f \\\nbun /root/.openclaw/agents/101/workspace/skills/baoyu-post-to-wechat/scripts/wechat-api.ts \\\n  /root/.openclaw/agents/101/workspace/post-to-wechat/2026-05-23/DeepSeek-V4Pro-降价-2026-05-23.md \\\n  --theme default --color blue \\\n  --author \"ai张三疯\" \\\n  --cover /root/.openclaw/agents/101/workspace/post-to-wechat/2026-05-23/imgs/deepseek-cover.jpg \\\n  2>&1","timeout":120}}],"api":"openai-completions","provider":"deepseek","model":"deepseek-chat","usage":{"input":284,"output":374,"cacheRead":27776,"cacheWrite":0,"totalTokens":28434,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"toolUse","timestamp":1779517978960,"responseId":"a7f22825-8044-453e-bb26-7824bb7082fc"}}
{"type":"message","id":"fd439b3d","parentId":"554001b6","timestamp":"2026-05-23T06:33:12.230Z","message":{"role":"toolResult","toolCallId":"call_00_H9SK1pqU6Bcs3f31tOqD7076","toolName":"exec","content":[{"type":"text","text":"Command still running (session ember-ocean, pid 1081868). Use process (list/poll/log/write/kill/clear/remove) for follow-up."}],"details":{"status":"running","sessionId":"ember-ocean","pid":1081868,"startedAt":1779517982168,"cwd":"/root/.openclaw/workspace/fabu","tail":"[wechat-api] Theme: default, color: blue, citeStatus: true\n[wechat-api] Rendering markdown with placeholders via md-to-wechat: default, color: blue, citeStatus: true\n[wechat-api] HTML generated: /tmp/wechat-article-images-2DfCfP/temp-article.html\n[wechat-api] Placeholder images: 1\n[wechat-api] Title: 不是促销，是屠刀：DeepSeek 把 API 价格永久砍掉 75%，整个行业被迫接招\n[wechat-api] Author: ai张三疯\n[wechat-api] Digest: 5月22日下午，你像往常一样打开 DeepSeek 官网，准备查一下 V4 Pro 的 API 定价...\n[wechat-api] Type: news\n[wechat-api] Account: 创业张三疯 (chuangyezhangsanfeng)\n[wechat-api] Fetching access token...\n[wechat-api] Uploading images...\n[wechat-api] Uploading placeholder image: /root/imgs/ads/OPC一人公司/1.jpg\n"},"isError":false,"timestamp":1779517992229}}
{"type":"message","id":"236b98e6","parentId":"fd439b3d","timestamp":"2026-05-23T06:33:18.365Z","message":{"role":"assistant","content":[{"type":"toolCall","id":"call_00_lTAVpasZ97MgIKB2AFma5760","name":"process","arguments":{"action":"poll","sessionId":"ember-ocean","timeout":60000}}],"api":"openai-completions","provider":"deepseek","model":"deepseek-chat","usage":{"input":65,"output":79,"cacheRead":28416,"cacheWrite":0,"totalTokens":28560,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"toolUse","timestamp":1779517992231,"responseId":"2fa0a0bf-a01b-4d00-94a2-530c3303f0bc"}}
{"type":"message","id":"894476ba","parentId":"236b98e6","timestamp":"2026-05-23T06:33:25.776Z","message":{"role":"toolResult","toolCallId":"call_00_lTAVpasZ97MgIKB2AFma5760","toolName":"process","content":[{"type":"text","text":"[wechat-api] Theme: default, color: blue, citeStatus: true\n[wechat-api] Rendering markdown with placeholders via md-to-wechat: default, color: blue, citeStatus: true\n[wechat-api] HTML generated: /tmp/wechat-article-images-2DfCfP/temp-article.html\n[wechat-api] Placeholder images: 1\n[wechat-api] Title: 不是促销，是屠刀：DeepSeek 把 API 价格永久砍掉 75%，整个行业被迫接招\n[wechat-api] Author: ai张三疯\n[wechat-api] Digest: 5月22日下午，你像往常一样打开 DeepSeek 官网，准备查一下 V4 Pro 的 API 定价...\n[wechat-api] Type: news\n[wechat-api] Account: 创业张三疯 (chuangyezhangsanfeng)\n[wechat-api] Fetching access token...\n[wechat-api] Uploading images...\n[wechat-api] Uploading placeholder image: /root/imgs/ads/OPC一人公司/1.jpg\n[wechat-api] Uploading cover: /root/.openclaw/agents/101/workspace/post-to-wechat/2026-05-23/imgs/deepseek-cover.jpg\n[wechat-api] Publishing to draft...\n{\n  \"success\": true,\n  \"media_id\": \"imBwNhfy9Uv4ps2luE5gfsJM254ksotUIG8ZaUslrzTm-tW9-MMPMd8KMEusOgzu\",\n  \"title\": \"不是促销，是屠刀：DeepSeek 把 API 价格永久砍掉 75%，整个行业被迫接招\",\n  \"articleType\": \"news\"\n}\n[wechat-api] Published successfully! media_id: imBwNhfy9Uv4ps2luE5gfsJM254ksotUIG8ZaUslrzTm-tW9-MMPMd8KMEusOgzu\n\nProcess exited with code 0."}],"details":{"status":"completed","sessionId":"ember-ocean","exitCode":0,"aggregated":"[wechat-api] Theme: default, color: blue, citeStatus: true\n[wechat-api] Rendering markdown with placeholders via md-to-wechat: default, color: blue, citeStatus: true\n[wechat-api] HTML generated: /tmp/wechat-article-images-2DfCfP/temp-article.html\n[wechat-api] Placeholder images: 1\n[wechat-api] Title: 不是促销，是屠刀：DeepSeek 把 API 价格永久砍掉 75%，整个行业被迫接招\n[wechat-api] Author: ai张三疯\n[wechat-api] Digest: 5月22日下午，你像往常一样打开 DeepSeek 官网，准备查一下 V4 Pro 的 API 定价...\n[wechat-api] Type: news\n[wechat-api] Account: 创业张三疯 (chuangyezhangsanfeng)\n[wechat-api] Fetching access token...\n[wechat-api] Uploading images...\n[wechat-api] Uploading placeholder image: /root/imgs/ads/OPC一人公司/1.jpg\n[wechat-api] Uploading cover: /root/.openclaw/agents/101/workspace/post-to-wechat/2026-05-23/imgs/deepseek-cover.jpg\n[wechat-api] Publishing to draft...\n{\n  \"success\": true,\n  \"media_id\": \"imBwNhfy9Uv4ps2luE5gfsJM254ksotUIG8ZaUslrzTm-tW9-MMPMd8KMEusOgzu\",\n  \"title\": \"不是促销，是屠刀：DeepSeek 把 API 价格永久砍掉 75%，整个行业被迫接招\",\n  \"articleType\": \"news\"\n}\n[wechat-api] Published successfully! media_id: imBwNhfy9Uv4ps2luE5gfsJM254ksotUIG8ZaUslrzTm-tW9-MMPMd8KMEusOgzu\n","name":"WECHAT_APP_ID=wx88b0cf376e0386c4 \\"},"isError":false,"timestamp":1779518005776}}
{"type":"message","id":"f4909b30","parentId":"894476ba","timestamp":"2026-05-23T06:33:30.175Z","message":{"role":"assistant","content":[{"type":"text","text":"✅ **Task 1 complete!** WeChat article published to draft. Let me verify by checking the draft list with batchget:"},{"type":"toolCall","id":"call_00_vKfWlXxJzjOrROCbBDSq7437","name":"exec","arguments":{"command":"cat << 'ENDCHECK' > /tmp/check-drafts.sh\n#!/bin/bash\n# Use curl to verify draft exists in WeChat draft box\nTOKEN=$(curl -s \"https://api.weixin.qq.com/cgi-bin/token?grant_type=client_credential&appid=wx88b0cf376e0386c4&secret=b2d47ee298204c28cf82549d2798192f\" | python3 -c \"import sys,json; print(json.load(sys.stdin).get('access_token',''))\")\nif [ -z \"$TOKEN\" ]; then echo \"Failed to get token\"; exit 1; fi\n\necho \"Access Token: ${TOKEN:0:10}...\"\n\nRESULT=$(curl -s -X POST \"https://api.weixin.qq.com/cgi-bin/draft/batchget?access_token=$TOKEN\" \\\n  -H \"Content-Type: application/json\" \\\n  -d '{\"offset\":0,\"count\":10,\"no_content\":1}')\necho \"Draft box query:\"\necho \"$RESULT\" | python3 -c \"\nimport sys, json\ndata = json.load(sys.stdin)\nif data.get('errcode'):\n    print(f'Error: {data}')\nelse:\n    items = data.get('items', [])\n    print(f'Total drafts: {data.get(\\\"total_count\\\", 0)}')\n    found = False\n    for i, item in enumerate(items):\n        title = item.get('title', 'N/A')\n        media_id = item.get('media_id', 'N/A')\n        update_time = item.get('update_time', 'N/A')\n        if 'DeepSeek' in title:\n            print(f'  ✅ FOUND: {title}')\n            print(f'     media_id: {media_id}')\n            found = True\n        else:\n            print(f'  {i+1}. {title}')\n    if not found:\n        print('  ⚠️ Article not found in first 10 drafts')\n\"\nENDCHECK\nbash /tmp/check-drafts.sh","timeout":30}}],"api":"openai-completions","provider":"deepseek","model":"deepseek-chat","usage":{"input":473,"output":527,"cacheRead":28544,"cacheWrite":0,"totalTokens":29544,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"toolUse","timestamp":1779518005777,"responseId":"b37b5dfd-567f-49ad-a9c3-7a00f9f9ad4d"}}
{"type":"message","id":"99c7bfdf","parentId":"f4909b30","timestamp":"2026-05-23T06:33:40.305Z","message":{"role":"toolResult","toolCallId":"call_00_vKfWlXxJzjOrROCbBDSq7437","toolName":"exec","content":[{"type":"text","text":"Command still running (session delta-daisy, pid 1081924). Use process (list/poll/log/write/kill/clear/remove) for follow-up."}],"details":{"status":"running","sessionId":"delta-daisy","pid":1081924,"startedAt":1779518010244,"cwd":"/root/.openclaw/workspace/fabu","tail":"Access Token: 104_yv9NZZ...\n"},"isError":false,"timestamp":1779518020305}}
{"type":"message","id":"a49b4601","parentId":"99c7bfdf","timestamp":"2026-05-23T06:33:41.465Z","message":{"role":"assistant","content":[{"type":"toolCall","id":"call_00_gchi8Yir0OiW9SIfHu0n6091","name":"process","arguments":{"sessionId":"delta-daisy","timeout":20000,"action":"poll"}}],"api":"openai-completions","provider":"deepseek","model":"deepseek-chat","usage":{"input":150,"output":79,"cacheRead":29440,"cacheWrite":0,"totalTokens":29669,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"toolUse","timestamp":1779518020307,"responseId":"f07d7fb0-6d88-413c-9af0-4bfee16810ab"}}
{"type":"message","id":"f3371ed5","parentId":"a49b4601","timestamp":"2026-05-23T06:33:42.063Z","message":{"role":"toolResult","toolCallId":"call_00_gchi8Yir0OiW9SIfHu0n6091","toolName":"process","content":[{"type":"text","text":"Access Token: 104_yv9NZZ...\nDraft box query:\nTotal drafts: 128\n  ⚠️ Article not found in first 10 drafts\n\nProcess exited with code 0."}],"details":{"status":"completed","sessionId":"delta-daisy","exitCode":0,"aggregated":"Access Token: 104_yv9NZZ...\nDraft box query:\nTotal drafts: 128\n  ⚠️ Article not found in first 10 drafts\n","name":"cat <<"},"isError":false,"timestamp":1779518022063}}
{"type":"message","id":"631904e6","parentId":"f3371ed5","timestamp":"2026-05-23T06:33:45.057Z","message":{"role":"assistant","content":[{"type":"text","text":"There are 128 drafts. Let me search more deeply:"},{"type":"toolCall","id":"call_00_t4joqWl0L9Yuzn27O6zn0390","name":"exec","arguments":{"command":"TOKEN=$(curl -s \"https://api.weixin.qq.com/cgi-bin/token?grant_type=client_credential&appid=wx88b0cf376e0386c4&secret=b2d47ee298204c28cf82549d2798192f\" | python3 -c \"import sys,json; print(json.load(sys.stdin).get('access_token',''))\")\n\n# Check pages of drafts\nfor offset in 0 10 20 30 40 50; do\n  RESULT=$(curl -s -X POST \"https://api.weixin.qq.com/cgi-bin/draft/batchget?access_token=$TOKEN\" \\\n    -H \"Content-Type: application/json\" \\\n    -d \"{\\\"offset\\\":$offset,\\\"count\\\":10,\\\"no_content\\\":1}\")\n  echo \"$RESULT\" | python3 -c \"\nimport sys, json\ndata = json.load(sys.stdin)\nif data.get('errcode'):\n    pass\nelse:\n    items = data.get('items', [])\n    for i, item in enumerate(items):\n        title = item.get('title', 'N/A')\n        if 'DeepSeek' in title or '降价' in title or '屠刀' in title:\n            mid = item.get('media_id', '')\n            print(f'  ✅ FOUND offset=$offset idx={i}: {title}')\n            print(f'     media_id: {mid}')\n\"\ndone\necho \"Done searching\"","timeout":30}}],"api":"openai-completions","provider":"deepseek","model":"deepseek-chat","usage":{"input":155,"output":389,"cacheRead":29568,"cacheWrite":0,"totalTokens":30112,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"toolUse","timestamp":1779518022064,"responseId":"8f2a374c-7144-4721-a22a-77064244c5a9"}}
{"type":"message","id":"22b5df10","parentId":"631904e6","timestamp":"2026-05-23T06:33:55.168Z","message":{"role":"toolResult","toolCallId":"call_00_t4joqWl0L9Yuzn27O6zn0390","toolName":"exec","content":[{"type":"text","text":"Command still running (session keen-atlas, pid 1081937). Use process (list/poll/log/write/kill/clear/remove) for follow-up."}],"details":{"status":"running","sessionId":"keen-atlas","pid":1081937,"startedAt":1779518025105,"cwd":"/root/.openclaw/workspace/fabu","tail":""},"isError":false,"timestamp":1779518035168}}
{"type":"message","id":"085f1cda","parentId":"22b5df10","timestamp":"2026-05-23T06:33:56.416Z","message":{"role":"assistant","content":[{"type":"toolCall","id":"call_00_AFJ8svjznVbAQKhkeHuk2060","name":"process","arguments":{"sessionId":"keen-atlas","timeout":30000,"action":"poll"}}],"api":"openai-completions","provider":"deepseek","model":"deepseek-chat","usage":{"input":78,"output":79,"cacheRead":30080,"cacheWrite":0,"totalTokens":30237,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"toolUse","timestamp":1779518035170,"responseId":"e7e9a2c0-4dd1-41fc-bd33-835edc4eabac"}}
{"type":"message","id":"dd7d43b1","parentId":"085f1cda","timestamp":"2026-05-23T06:34:06.338Z","message":{"role":"toolResult","toolCallId":"call_00_AFJ8svjznVbAQKhkeHuk2060","toolName":"process","content":[{"type":"text","text":"Done searching\n\nProcess exited with code 0."}],"details":{"status":"completed","sessionId":"keen-atlas","exitCode":0,"aggregated":"Done searching\n","name":"TOKEN=$(curl https://api.weixin.qq....204c28cf82549d2798192f"},"isError":false,"timestamp":1779518046338}}
{"type":"message","id":"736773c3","parentId":"dd7d43b1","timestamp":"2026-05-23T06:34:10.189Z","message":{"role":"assistant","content":[{"type":"text","text":"Hmm, no results found across first 60 drafts. Let me check the total count again and also search by the specific media_id:"},{"type":"toolCall","id":"call_00_Ko86c2nAx0LR2S6yqWUp6597","name":"exec","arguments":{"command":"TOKEN=$(curl -s \"https://api.weixin.qq.com/cgi-bin/token?grant_type=client_credential&appid=wx88b0cf376e0386c4&secret=b2d47ee298204c28cf82549d2798192f\" | python3 -c \"import sys,json; print(json.load(sys.stdin).get('access_token',''))\")\n\necho \"=== Total count ===\"\ncurl -s -X POST \"https://api.weixin.qq.com/cgi-bin/draft/batchget?access_token=$TOKEN\" \\\n  -H \"Content-Type: application/json\" \\\n  -d '{\"offset\":0,\"count\":1,\"no_content\":1}' | python3 -c \"import sys,json; d=json.load(sys.stdin); print(f'Total: {d.get(\\\"total_count\\\",\\\"?\\\")}')\"\n\n# Try with content included to see more info\necho \"=== check by content ===\"\ncurl -s -X POST \"https://api.weixin.qq.com/cgi-bin/draft/get?access_token=$TOKEN\" \\\n  -H \"Content-Type: application/json\" \\\n  -d '{\"media_id\":\"imBwNhfy9Uv4ps2luE5gfsJM254ksotUIG8ZaUslrzTm-tW9-MMPMd8KMEusOgzu\"}' \\\n  | python3 -c \"\nimport sys, json\nd = json.load(sys.stdin)\nif 'errcode' in d:\n    print(f'Error: {d}')\nelse:\n    print(f'Title: {d.get(\\\"news_item\\\",[{}])[0].get(\\\"title\\\",\\\"N/A\\\")}')\n    print(f'Status: VERIFIED ✅')\n\"","timeout":20}}],"api":"openai-completions","provider":"deepseek","model":"deepseek-chat","usage":{"input":50,"output":471,"cacheRead":30208,"cacheWrite":0,"totalTokens":30729,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"toolUse","timestamp":1779518046340,"responseId":"471cf987-32ab-4656-8893-8758a93c0e0a"}}
{"type":"message","id":"4d29cbd5","parentId":"736773c3","timestamp":"2026-05-23T06:34:11.965Z","message":{"role":"toolResult","toolCallId":"call_00_Ko86c2nAx0LR2S6yqWUp6597","toolName":"exec","content":[{"type":"text","text":"=== Total count ===\nTotal: 128\n=== check by content ===\nTitle: 不是促销，是屠刀：DeepSeek 把 API 价格永久砍掉 75%，整个行业被迫接招\nStatus: VERIFIED ✅"}],"details":{"status":"completed","exitCode":0,"durationMs":1680,"aggregated":"=== Total count ===\nTotal: 128\n=== check by content ===\nTitle: 不是促销，是屠刀：DeepSeek 把 API 价格永久砍掉 75%，整个行业被迫接招\nStatus: VERIFIED ✅","cwd":"/root/.openclaw/workspace/fabu"},"isError":false,"timestamp":1779518051965}}
{"type":"message","id":"23714aa7","parentId":"4d29cbd5","timestamp":"2026-05-23T06:34:15.527Z","message":{"role":"assistant","content":[{"type":"text","text":"The article is confirmed in the draft box. It just wasn't showing in the first 60 because there are 128 drafts. Could be further down. But the direct get by media_id confirms it exists. Let me search more thoroughly:"},{"type":"toolCall","id":"call_00_Hhtpnf7spzxQwMx6lATj8731","name":"exec","arguments":{"command":"TOKEN=$(curl -s \"https://api.weixin.qq.com/cgi-bin/token?grant_type=client_credential&appid=wx88b0cf376e0386c4&secret=b2d47ee298204c28cf82549d2798192f\" | python3 -c \"import sys,json; print(json.load(sys.stdin).get('access_token',''))\")\n\n# Check remaining pages\nfor offset in 60 70 80 90 100 110 120; do\n  RESULT=$(curl -s -X POST \"https://api.weixin.qq.com/cgi-bin/draft/batchget?access_token=$TOKEN\" \\\n    -H \"Content-Type: application/json\" \\\n    -d \"{\\\"offset\\\":$offset,\\\"count\\\":10,\\\"no_content\\\":1}\")\n  echo \"$RESULT\" | python3 -c \"\nimport sys, json\ndata = json.load(sys.stdin)\nif data.get('errcode'):\n    pass\nelse:\n    items = data.get('items', [])\n    for i, item in enumerate(items):\n        title = item.get('title', 'N/A')\n        mid = item.get('media_id', '')\n        print(f'  offset=$offset idx={i}: {title} | {mid}')\n\"\ndone","timeout":30}}],"api":"openai-completions","provider":"deepseek","model":"deepseek-chat","usage":{"input":72,"output":387,"cacheRead":30720,"cacheWrite":0,"totalTokens":31179,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"toolUse","timestamp":1779518051966,"responseId":"135ff7eb-56f9-44ae-88f8-9450c6f4cad4"}}
{"type":"message","id":"64b4c9ca","parentId":"23714aa7","timestamp":"2026-05-23T06:34:25.638Z","message":{"role":"toolResult","toolCallId":"call_00_Hhtpnf7spzxQwMx6lATj8731","toolName":"exec","content":[{"type":"text","text":"Command still running (session good-breeze, pid 1082012). Use process (list/poll/log/write/kill/clear/remove) for follow-up."}],"details":{"status":"running","sessionId":"good-breeze","pid":1082012,"startedAt":1779518055577,"cwd":"/root/.openclaw/workspace/fabu","tail":""},"isError":false,"timestamp":1779518065637}}
{"type":"message","id":"0dfcf95d","parentId":"64b4c9ca","timestamp":"2026-05-23T06:34:31.689Z","message":{"role":"assistant","content":[{"type":"toolCall","id":"call_00_9tILFGnm6T1eRghuglk31658","name":"process","arguments":{"sessionId":"good-breeze","timeout":45000,"action":"poll"}}],"api":"openai-completions","provider":"deepseek","model":"deepseek-chat","usage":{"input":121,"output":79,"cacheRead":31104,"cacheWrite":0,"totalTokens":31304,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"toolUse","timestamp":1779518065639,"responseId":"78bc6af5-8815-402b-856a-e3eaac9aeb52"}}
{"type":"message","id":"966856bb","parentId":"0dfcf95d","timestamp":"2026-05-23T06:34:31.780Z","message":{"role":"toolResult","toolCallId":"call_00_9tILFGnm6T1eRghuglk31658","toolName":"process","content":[{"type":"text","text":"(no output recorded)\n\nProcess exited with code 0."}],"details":{"status":"completed","sessionId":"good-breeze","exitCode":0,"aggregated":"","name":"TOKEN=$(curl https://api.weixin.qq....204c28cf82549d2798192f"},"isError":false,"timestamp":1779518071779}}
{"type":"message","id":"d15d4cc9","parentId":"966856bb","timestamp":"2026-05-23T06:34:34.070Z","message":{"role":"assistant","content":[{"type":"text","text":"No output which means API error on those offsets (likely past the valid range). But we already confirmed via `draft/get` that the article exists with matching title. The article is in the draft box.\n\n✅ **Task 1: WeChat published successfully.**\n\nNow let me proceed with **Task 2: Website publishing.**\n\n**Step 2a:** Generate HTML from the source markdown:"},{"type":"toolCall","id":"call_00_VilHOeYbRttuCfuLJlSR2489","name":"exec","arguments":{"command":"python3 /root/.openclaw/agents/发布大师/workspace/scripts/md2html.py \\\n  /root/.openclaw/agents/文章大师/workspace/deepseek-permanent-price-cut-20260523-v1.md \\\n  -o /tmp/deepseek-price-cut.html 2>&1","timeout":15}}],"api":"openai-completions","provider":"deepseek","model":"deepseek-chat","usage":{"input":94,"output":206,"cacheRead":31232,"cacheWrite":0,"totalTokens":31532,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"toolUse","timestamp":1779518071781,"responseId":"2955c34f-81d6-4ed3-8463-76dc9fb7bc80"}}
{"type":"message","id":"30ee0aa7","parentId":"d15d4cc9","timestamp":"2026-05-23T06:34:34.357Z","message":{"role":"toolResult","toolCallId":"call_00_VilHOeYbRttuCfuLJlSR2489","toolName":"exec","content":[{"type":"text","text":"HTML 已保存到: /tmp/deepseek-price-cut.html\n标题: 不是促销，是屠刀：DeepSeek 把 API 价格永久砍掉 75%，整个行业被迫接招"}],"details":{"status":"completed","exitCode":0,"durationMs":189,"aggregated":"HTML 已保存到: /tmp/deepseek-price-cut.html\n标题: 不是促销，是屠刀：DeepSeek 把 API 价格永久砍掉 75%，整个行业被迫接招","cwd":"/root/.openclaw/workspace/fabu"},"isError":false,"timestamp":1779518074357}}
{"type":"message","id":"45eb7fb7","parentId":"30ee0aa7","timestamp":"2026-05-23T06:34:35.247Z","message":{"role":"assistant","content":[{"type":"toolCall","id":"call_00_aFJp9iJ44oKjZyM7rUDO3988","name":"read","arguments":{"path":"/tmp/deepseek-price-cut.html"}}],"api":"openai-completions","provider":"deepseek","model":"deepseek-chat","usage":{"input":100,"output":49,"cacheRead":31488,"cacheWrite":0,"totalTokens":31637,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"toolUse","timestamp":1779518074358,"responseId":"103a87d0-7afd-4fd4-83ad-c0e26c01c692"}}
{"type":"message","id":"d8dd80d9","parentId":"45eb7fb7","timestamp":"2026-05-23T06:34:35.349Z","message":{"role":"toolResult","toolCallId":"call_00_aFJp9iJ44oKjZyM7rUDO3988","toolName":"read","content":[{"type":"text","text":"<h1>不是促销，是屠刀：DeepSeek 把 API 价格永久砍掉 75%，整个行业被迫接招</h1>\n<p>想象你是某家AI创业公司的CTO。</p>\n<p>5月22日下午，你像往常一样打开 DeepSeek 官网，准备查一下 V4 Pro 的 API 定价。结果你愣住了：之前打2.5折的促销价，5月31日之后，直接变成永久正价。不是\"限时特惠\"，不是\"新用户福利\"。是官方主页上白纸黑字写着——降价75%，永久执行。</p>\n<p>你第一反应是什么？不是\"DeepSeek真大方\"。而是\"卧槽，那我的产品定价和商业模型要重新算了\"。</p>\n<p>这才是这则消息真正的杀伤力。</p>\n<h2 id=\"_1\">这招，比技术突破还狠</h2>\n<p>很多人的第一反应是：DeepSeek V4 Pro 又降价了？哦，促销活动而已。</p>\n<p>再看一眼。</p>\n<p>5月22日，DeepSeek 官方更新了 API 定价页面。清晰明确：deepseek-v4-pro 模型价格在结束2.5折优惠活动后，正式调整为原价的1/4。<strong>不是临时活动延续，而是永久性的标价调整。</strong></p>\n<p>翻译成人话：<strong>促销价变成了常规价。</strong> 之前你以为\"薅羊毛\"的窗口，现在变成了永久通道。</p>\n<p>这跟所有AI公司的套路都不一样。</p>\n<p>OpenAI、Google、Anthropic 都搞过降价。但它们的模式是\"限时优惠\"——给新用户送额度、推出轻量版降价、或者搞\"首月半价\"。本质上是<strong>营销战术</strong>，不是定价战略。优惠期一过，价格恢复原样，开发者老老实实继续交钱。</p>\n<p>DeepSeek 的做法完全反着来：把打折变成正价，把促→销变成永久降价。这意味着什么？</p>\n<p><strong>它的成本已经低到不需要\"恢复原价\"了。</strong></p>\n<p>这话如果从别人嘴里说出来，你可能不信。但 DeepSeek 从 V2 到 V4 Pro，价格一直在降，从未涨过。每一次降价都不是\"为了抢客户烧钱\"，而是技术优化后成本下降了，自然传导给用户。</p>\n<p>这次更狠——直接一刀剁掉 75%。</p>\n<h2 id=\"gpt-55\">跟 GPT-5.5 比，已经不是竞争，是屠杀</h2>\n<p>做AI应用的朋友都清楚一个问题：</p>\n<p>API 调用成本，从来不是\"用不用得起\"的问题，而是\"能不能撑起商业模型\"的问题。</p>\n<p>举个最简单的例子：假设你的AI应用，每次用户提问需要调用大模型生成回答。用 GPT-5.5，输出的边际成本是 X 元。用 DeepSeek V4 Pro，成本是 X 除以几十。</p>\n<p>如果你的应用是高频交互型的——比如AI客服、AI助手、AI教育——那几十倍的成本差距，直接决定了你的定价策略和利润空间能用多大的分水岭。</p>\n<p>GPT-5.5 用户每次对话你赚1毛，GPT-5.5 用户每次对话亏8分——成本差异就能把一条业务线从赚钱变成亏钱。</p>\n<p>而 DeepSeek V4 Pro 的降价，相当于把所有用GPT-5.5做应用的创业者都推到了一个选择题面前：<strong>要么换平台，成本降到原来的几十分之一；要么保持现状，眼睁睁看对手用更低的成本抢你的客户。</strong></p>\n<p>听起来残酷，但商业就是这样。</p>\n<h2 id=\"_2\">摩尔定律在大模型时代的变体</h2>\n<p>你可能要问：DeepSeek 凭什么能做到这么低的价格？</p>\n<p>答案不是什么\"中国公司人工便宜\"，而是<strong>全栈优化的累积效应</strong>。</p>\n<p>摩尔定律的历史告诉我们：芯片性能每18个月翻一倍，成本降一半。但那是硬件端的规律。</p>\n<p>大模型的成本下降，吃的是三块红利：</p>\n<p>第一块，<strong>模型架构层面的优化。</strong> DeepSeek 自研的 MoE（混合专家）架构，让每次推理只激活部分参数，不像 GPT-5.5 那样的稠密模型每问一次全量计算。这就好比开一盏灯，不用点亮整栋楼。</p>\n<p>第二块，<strong>训练-推理一体化。</strong> 很多AI公司的训练和推理是分离的团队、分离的架构。DeepSeek 从模型设计那天就考虑推理效率。训练阶段做的优化在推理阶段也能复用，效率叠加。</p>\n<p>第三块，<strong>部署层优化。</strong> 从底层算子到硬件调度，DeepSeek 的工程团队把每一层都做精了。看起来是\"降价75%\"的激进定价，背后是每一层的成本都砍了一刀。</p>\n<p><strong>只有真正掌控了从模型架构→训练→推理→部署全栈的公司，才能把降价转嫁给用户。</strong></p>\n<p>大多数AI公司要么只有模型层能力（研发强，工程弱），要么只有应用层能力（调API，不懂底层）。DeepSeek的可怕之处在于：它把整个链条都打通了，然后选择了一个最暴力的打法——价格战。</p>\n<h2 id=\"_3\">给创业者的信号：之前的借口，现在都不成立了</h2>\n<p>说实话，过去一年我跟不少做AI应用的人聊过。</p>\n<p>聊到为什么产品做得慢、为什么用户量上不去，十个里有七八个会说：\"没办法，API成本太高，跑不起大规模。\"</p>\n<p>这个借口，现在彻底废了。</p>\n<p>DeepSeek V4 Pro 把旗舰模型的价格打到了白菜价。按新的定价，你用它搭一个AI产品，边际成本已经低到可以忽略不计。以前\"API太贵\"是真实的障碍，现在这个障碍已经被铲平了。</p>\n<p>这意味着什么？</p>\n<p><strong>AI应用层的创业逻辑，需要重新写。</strong> 以前大家拼的是\"谁能烧得起推理成本\"。以后拼的是\"谁能做出用户真正想用的东西\"。</p>\n<p>场景创新、产品体验、用户留存——这些被成本问题压了两年的话题，现在可以真正提上日程了。</p>\n<p>如果你是一个做AI应用的创业者，现在最好的策略不是继续观望等下一轮降价。是立刻上手，用这个价格去验证你的商业模式。因为当API成本不再是天花板，你的天花板就是你的产品和运营能力。</p>\n<h2 id=\"_4\">整个行业，被迫接招</h2>\n<p>DeepSeek 这一刀，不只是打给开发者和企业看的。这一刀，是砍给整个AI行业看的。</p>\n<p>OpenAI、Google、Anthropic 现在面临一个两难选择：</p>\n<p><strong>要么跟牌降价，利润更薄。</strong></p>\n<p>GPT-5.5 的训练和推理成本结构跟 DeepSeek V4 Pro 完全不同。DeepSeek 是用 MoE 架构、全栈优化、以及相对更低的人力成本在支撑定价。OpenAI 想降到同样价位，要么压缩自己的利润空间，要么做更大的架构创新。两条路都不轻松。</p>\n<p><strong>要么不做降价，押注差异化。</strong></p>\n<p>赌的是\"品牌溢价\"、\"安全性\"、\"企业级服务\"这些DeepSeek比较薄弱的环节。不是不行，但前提是你得有足够多的企业客户愿意为这些溢价买单。当隔壁家便宜了几十倍，很多技术决策者会在董事会上被老板问：\"为什么我们不能用那个更便宜的？\"</p>\n<p>这场景，像极了当年的云计算价格战。AWS、Azure、Google Cloud 轮流降价，每个季度都比上个季度低一点。你降，他降，最后大家都降。</p>\n<p>但 DeepSeek 这次不是\"降一点\"，是直接降了四分之三。</p>\n<p>这已经不是在打价格战了。这是在重新定义\"公允价格\"。</p>\n<p>当整个行业的参考价被一家公司腰斩再腰斩，其他公司要么跟上，要么退到小众市场。没有中间地带。</p>\n<h2 id=\"_5\">时间节点，是精心算过的</h2>\n<p>5月22日发布，5月31日生效。</p>\n<p>一周时间。</p>\n<p>看起来是一个\"给用户过渡期\"，但仔细想想，这一周对DeepSeek来说，信息价值极大。</p>\n<p>5月22日到5月31日这7天，所有正在用GPT-5.5或者其他模型的企业，会怎么做？</p>\n<ul>\n<li>预算部门会算账：换成DeepSeek能省多少钱</li>\n<li>技术部门会测试：迁移需要多少工作量</li>\n<li>决策部门会开会：要不要换供应商</li>\n</ul>\n<p>DeepSeek 给了他们一周时间算这笔账。它不怕你算。它希望你算。</p>\n<p>因为不管你怎么算，结果都是：换过来，省一大笔钱。</p>\n<p>这7天，也是DeepSeek收割市场信号的窗口期。哪些企业最着急迁移，哪些行业对成本最敏感，哪些客户群体会跟着降价迁移——这些信息在7天后的定价生效日，会全部暴露。</p>\n<p>这不是一个简单的\"我们降价了\"的通知。这是一次精心设计的市场渗透行动。</p>\n<hr>\n<p>回到开头那个CTO的视角。</p>\n<p>当他缓过神来，拿起手机在群里发了一句：\"DeepSeek 这轮降价后，我们用什么理由继续用GPT-5.5？\"</p>\n<p>群里沉默了三秒，然后有人回了一句：</p>\n<p>\"没有理由了。\"</p>\n<p>这就是 DeepSeek 真正的胜利。不是你做不出更好的模型，而是你让所有用户都找不到继续用你的理由。</p>\n<p>一刀 75%，砍掉的不是价格。是竞争对手的市场防守底线。</p>\n"}],"isError":false,"timestamp":1779518075349}}
{"type":"message","id":"308f91ca","parentId":"d8dd80d9","timestamp":"2026-05-23T06:34:47.081Z","message":{"role":"assistant","content":[{"type":"text","text":"Good, HTML generated. Now Step 2b: Create the publish script. Note the md2html already stripped the front-matter and produced clean HTML. I need to append the poster image using the CDN URL from the ads-image-map."},{"type":"toolCall","id":"call_00_BEU9fB091x8ki4uEjWiP7877","name":"write","arguments":{"path":"/tmp/publish-deepseek-price-cut.js","content":"const https = require('https');\nconst http = require('http');\n\nconst ZBLOG_URL = 'https://weixinsiwei.com/zb_system/xml-rpc/index.php';\nconst USERNAME = 'admin';\nconst PASSWORD = '135269zxj';\nconst BLOG_ID = '68ba1ff10060dd54f1e399b8e332bdba';\n\n// Read HTML content\nconst fs = require('fs');\nconst htmlPath = '/tmp/deepseek-price-cut.html';\nlet htmlContent = fs.readFileSync(htmlPath, 'utf-8');\n\n// Add CDN ad poster at the end\nhtmlContent += '\\n\\n<hr>\\n<p><strong>一人公司，从想法到赚钱，其实没有那么难。</strong></p>\\n<p><img src=\"https://weixinsiwei.com/zb_users/upload/2026/05/84850393b2efb63633d3fdfd9a6e21b4.jpg\" alt=\"广告海报\"></p>\\n';\n\nconst title = '不是促销，是屠刀：DeepSeek 把 API 价格永久砍掉 75%，整个行业被迫接招';\nconst categories = ['ai-app'];\n\n// Build XML-RPC request\nfunction buildMetaWeblogPost(title, content, categories) {\n  return `<?xml version=\"1.0\"?>\n<methodCall>\n  <methodName>metaWeblog.newPost</methodName>\n  <params>\n    <param><value><string>${BLOG_ID}</string></value></param>\n    <param><value><string>${USERNAME}</string></value></param>\n    <param><value><string>${PASSWORD}</string></value></param>\n    <param>\n      <value>\n        <struct>\n          <member>\n            <name>title</name>\n            <value><string>${escapeXml(title)}</string></value>\n          </member>\n          <member>\n            <name>description</name>\n            <value><string>${escapeXml(content)}</string></value>\n          </member>\n          <member>\n            <name>categories</name>\n            <value>\n              <array>\n                <data>\n                  ${categories.map(c => `<value><string>${escapeXml(c)}</string></value>`).join('\\n                  ')}\n                </data>\n              </array>\n            </value>\n          </member>\n          <member>\n            <name>mt_keywords</name>\n            <value><string>DeepSeek,AI,降价,创业,API,价格战,大模型</string></value>\n          </member>\n        </struct>\n      </value>\n    </param>\n    <param><value><boolean>1</boolean></value></param>\n  </params>\n</methodCall>`;\n}\n\nfunction buildGetRecentPosts() {\n  return `<?xml version=\"1.0\"?>\n<methodCall>\n  <methodName>metaWeblog.getRecentPosts</methodName>\n  <params>\n    <param><value><string>${BLOG_ID}</string></value></param>\n    <param><value><string>${USERNAME}</string></value></param>\n    <param><value><string>${PASSWORD}</string></value></param>\n    <param><value><int>5</int></value></param>\n  </params>\n</methodCall>`;\n}\n\nfunction escapeXml(str) {\n  return str.replace(/&/g, '&amp;')\n    .replace(/</g, '&lt;')\n    .replace(/>/g, '&gt;')\n    .replace(/\"/g, '&quot;')\n    .replace(/'/g, '&apos;');\n}\n\nfunction sendXmlRpc(url, xmlBody) {\n  return new Promise((resolve, reject) => {\n    const urlObj = new URL(url);\n    const mod = urlObj.protocol === 'https:' ? https : http;\n    \n    const options = {\n      hostname: urlObj.hostname,\n      port: urlObj.port || (urlObj.protocol === 'https:' ? 443 : 80),\n      path: urlObj.pathname,\n      method: 'POST',\n      headers: {\n        'Content-Type': 'text/xml; charset=utf-8',\n        'Content-Length': Buffer.byteLength(xmlBody, 'utf-8'),\n        'User-Agent': 'OpenClaw-Publisher/1.0',\n      },\n    };\n    \n    const req = mod.request(options, (res) => {\n      let data = '';\n      res.on('data', (chunk) => data += chunk);\n      res.on('end', () => resolve({ status: res.statusCode, data }));\n    });\n    \n    req.on('error', reject);\n    req.write(xmlBody, 'utf-8');\n    req.end();\n  });\n}\n\nasync function main() {\n  console.log('=== Publishing to Z-Blog ===');\n  console.log(`URL: ${ZBLOG_URL}`);\n  console.log(`Title: ${title}`);\n  console.log(`Categories: ${categories.join(', ')}`);\n  \n  // Step 1: Publish\n  const postXml = buildMetaWeblogPost(title, htmlContent, categories);\n  console.log('\\n--- Publishing new post ---');\n  const publishResult = await sendXmlRpc(ZBLOG_URL, postXml);\n  console.log(`Status: ${publishResult.status}`);\n  console.log(`Response: ${publishResult.data.substring(0, 1000)}`);\n  \n  if (publishResult.status === 200 && publishResult.data.includes('fault')) {\n    console.error('ERROR: Server returned fault response');\n    process.exit(1);\n  }\n  \n  // newPost in Z-Blog only returns boolean (true/false), not post ID\n  const success = publishResult.data.includes('<boolean>1</boolean>') || \n                  publishResult.data.includes('<boolean>true') ||\n                  publishResult.data.includes('<i4>');\n  console.log(`\\n✅ Publish result: ${success ? 'SUCCESS' : 'Check response above'}`);\n  \n  // Step 2: Verify with getRecentPosts\n  console.log('\\n--- Verifying with getRecentPosts ---');\n  const verifyXml = buildGetRecentPosts();\n  const verifyResult = await sendXmlRpc(ZBLOG_URL, verifyXml);\n  console.log(`Status: ${verifyResult.status}`);\n  \n  // Extract post titles from response\n  const titleRegex = /<name>title<\\/name>\\s*<value>\\s*<string>([^<]+)<\\/string>/g;\n  let match;\n  const titles = [];\n  while ((match = titleRegex.exec(verifyResult.data)) !== null) {\n    titles.push(match[1]);\n  }\n  \n  console.log(`\\nRecent posts (${titles.length} found):`);\n  titles.forEach((t, i) => console.log(`  ${i + 1}. ${t}`));\n  \n  if (titles.some(t => t.includes('DeepSeek') || t.includes('降价'))) {\n    console.log('\\n✅ Verification passed: Article found in recent posts!');\n  } else {\n    console.log('\\n⚠️ Warning: Article not found in recent posts');\n    // Check response for post ID\n    const idMatch = verifyResult.data.match(/<name>postid<\\/name>\\s*<value>\\s*<string>([^<]+)<\\/string>/);\n    if (idMatch) {\n      console.log(`Post ID from response: ${idMatch[1]}`);\n    }\n    console.log('Full response snippet:', verifyResult.data.substring(0, 500));\n  }\n}\n\nmain().catch(err => {\n  console.error('Error:', err);\n  process.exit(1);\n});\n"}}],"api":"openai-completions","provider":"deepseek","model":"deepseek-chat","usage":{"input":2278,"output":1767,"cacheRead":31616,"cacheWrite":0,"totalTokens":35661,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"toolUse","timestamp":1779518075351,"responseId":"de2dc5bb-9623-4a4b-804e-0795e1503f4f"}}
{"type":"message","id":"ea40a08a","parentId":"308f91ca","timestamp":"2026-05-23T06:34:47.176Z","message":{"role":"toolResult","toolCallId":"call_00_BEU9fB091x8ki4uEjWiP7877","toolName":"write","content":[{"type":"text","text":"Successfully wrote 5736 bytes to /tmp/publish-deepseek-price-cut.js"}],"isError":false,"timestamp":1779518087175}}
{"type":"message","id":"5deb8962","parentId":"ea40a08a","timestamp":"2026-05-23T06:34:48.345Z","message":{"role":"assistant","content":[{"type":"toolCall","id":"call_00_AwDS8uCFUe8XLZlMlzm16436","name":"exec","arguments":{"command":"node /tmp/publish-deepseek-price-cut.js 2>&1","timeout":30}}],"api":"openai-completions","provider":"deepseek","model":"deepseek-chat","usage":{"input":107,"output":73,"cacheRead":35584,"cacheWrite":0,"totalTokens":35764,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"toolUse","timestamp":1779518087177,"responseId":"662e3423-3e66-41bf-a127-bcdf345047a5"}}
{"type":"message","id":"b053ce8d","parentId":"5deb8962","timestamp":"2026-05-23T06:34:49.442Z","message":{"role":"toolResult","toolCallId":"call_00_AwDS8uCFUe8XLZlMlzm16436","toolName":"exec","content":[{"type":"text","text":"=== Publishing to Z-Blog ===\nURL: https://weixinsiwei.com/zb_system/xml-rpc/index.php\nTitle: 不是促销，是屠刀：DeepSeek 把 API 价格永久砍掉 75%，整个行业被迫接招\nCategories: ai-app\n\n--- Publishing new post ---\nStatus: 200\nResponse: <methodResponse><params><param><value><boolean>1</boolean></value></param></params></methodResponse>\n\n✅ Publish result: SUCCESS\n\n--- Verifying with getRecentPosts ---\nStatus: 200\n\nRecent posts (5 found):\n  1. 不是促销，是屠刀：DeepSeek 把 API 价格永久砍掉 75%，整个行业被迫接招\n  2. 124米巨兽升空，却丢了助推器：星舰V3首飞的得与失，藏着SpaceX IPO的所有秘密\n  3. 跨境券商重罚\n  4. AI隐形总指挥\n  5. 新职业诞生：文创产品策划运营师正式&amp;quot;入编&amp;quot;，这波红利你接不接？\n\n✅ Verification passed: Article found in recent posts!"}],"details":{"status":"completed","exitCode":0,"durationMs":1007,"aggregated":"=== Publishing to Z-Blog ===\nURL: https://weixinsiwei.com/zb_system/xml-rpc/index.php\nTitle: 不是促销，是屠刀：DeepSeek 把 API 价格永久砍掉 75%，整个行业被迫接招\nCategories: ai-app\n\n--- Publishing new post ---\nStatus: 200\nResponse: <methodResponse><params><param><value><boolean>1</boolean></value></param></params></methodResponse>\n\n✅ Publish result: SUCCESS\n\n--- Verifying with getRecentPosts ---\nStatus: 200\n\nRecent posts (5 found):\n  1. 不是促销，是屠刀：DeepSeek 把 API 价格永久砍掉 75%，整个行业被迫接招\n  2. 124米巨兽升空，却丢了助推器：星舰V3首飞的得与失，藏着SpaceX IPO的所有秘密\n  3. 跨境券商重罚\n  4. AI隐形总指挥\n  5. 新职业诞生：文创产品策划运营师正式&amp;quot;入编&amp;quot;，这波红利你接不接？\n\n✅ Verification passed: Article found in recent posts!","cwd":"/root/.openclaw/workspace/fabu"},"isError":false,"timestamp":1779518089442}}
{"type":"message","id":"0bdbb593","parentId":"b053ce8d","timestamp":"2026-05-23T06:34:51.402Z","message":{"role":"assistant","content":[{"type":"text","text":"Both published successfully and verified! Now Step 2c: Delete the temporary script file."},{"type":"toolCall","id":"call_00_bLTcZSBRPeeBLUQLMG5w8259","name":"exec","arguments":{"command":"rm /tmp/publish-deepseek-price-cut.js && echo \"Temp script deleted\""}}],"api":"openai-completions","provider":"deepseek","model":"deepseek-chat","usage":{"input":316,"output":76,"cacheRead":35712,"cacheWrite":0,"totalTokens":36104,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"toolUse","timestamp":1779518089446,"responseId":"bc6a567d-cfbe-43fc-9570-d4b56084cf27"}}
{"type":"message","id":"f8075962","parentId":"0bdbb593","timestamp":"2026-05-23T06:34:51.613Z","message":{"role":"toolResult","toolCallId":"call_00_bLTcZSBRPeeBLUQLMG5w8259","toolName":"exec","content":[{"type":"text","text":"Temp script deleted"}],"details":{"status":"completed","exitCode":0,"durationMs":57,"aggregated":"Temp script deleted","cwd":"/root/.openclaw/workspace/fabu"},"isError":false,"timestamp":1779518091613}}
{"type":"message","id":"8985d211","parentId":"f8075962","timestamp":"2026-05-23T06:34:54.707Z","message":{"role":"assistant","content":[{"type":"text","text":"## 发布结果报告\n\n### ✅ 任务1：公众号发布 — 成功\n- **公众号：** 创业张三疯 (chuangyezhangsanfeng)\n- **标题：** 不是促销，是屠刀：DeepSeek 把 API 价格永久砍掉 75%，整个行业被迫接招\n- **作者：** ai张三疯\n- **media_id：** `imBwNhfy9Uv4ps2luE5gfsJM254ksotUIG8ZaUslrzTm-tW9-MMPMd8KMEusOgzu`\n- **验证：** ✅ 已通过 `draft/get` 确认文章在草稿箱中，标题匹配\n\n### ✅ 任务2：网站发布 — 成功\n- **网站：** weixinsiwei.com (创业思维网)\n- **标题：** 不是促销，是屠刀：DeepSeek 把 API 价格永久砍掉 75%，整个行业被迫接招\n- **分类：** ai-app\n- **验证：** ✅ `metaWeblog.getRecentPosts` 返回列表中第一条即为该文章，确认发布成功\n- **海报：** 已追加 OPC一人公司广告海报（CDN地址）\n- **临时脚本：** 已删除"}],"api":"openai-completions","provider":"deepseek","model":"deepseek-chat","usage":{"input":23,"output":274,"cacheRead":36096,"cacheWrite":0,"totalTokens":36393,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1779518091614,"responseId":"c298d45c-0cc1-4a7d-b9fb-1da6cb0b292e"}}