<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>AI Tools on Mi&amp;Bee Blog</title><link>/en/categories/ai-tools/</link><description>Recent content in AI Tools on Mi&amp;Bee Blog</description><generator>Hugo -- gohugo.io</generator><language>en</language><managingEditor>蓝宝石的傻话</managingEditor><lastBuildDate>Fri, 15 May 2026 00:00:00 +0000</lastBuildDate><atom:link href="/en/categories/ai-tools/rss.xml" rel="self" type="application/rss+xml"/><item><title>The Hidden Trap of Headless Browsers: Why Can't Your Automation Tool Catch Early Page Errors?</title><link>/en/posts/aihelper/headless-browser-early-error-capture/</link><pubDate>Fri, 15 May 2026 00:00:00 +0000</pubDate><guid>/en/posts/aihelper/headless-browser-early-error-capture/</guid><description>&lt;h2 id="introduction"&gt;Introduction&lt;/h2&gt;
&lt;p&gt;You&amp;rsquo;re debugging a frontend engineering issue — the page is behaving abnormally. You ask an AI to open the page with a browser tool and check the console for errors.&lt;/p&gt;
&lt;p&gt;The AI opens the page, scans around, and tells you: &lt;strong&gt;The console is clean, no errors whatsoever.&lt;/strong&gt;&lt;/p&gt;
&lt;p&gt;You&amp;rsquo;re skeptical. You open Chrome DevTools yourself — three bright red errors are staring you in the face, the page has already crashed into a white screen. The AI visited the exact same page using a Headless browser, &lt;strong&gt;so why did it catch nothing?&lt;/strong&gt;&lt;/p&gt;</description></item><item><title>One Month with the Zhi Theme: Mermaid v11 Upgrade Experience</title><link>/en/posts/aihelper/hugo-theme-zhi-v11-upgrade/</link><pubDate>Wed, 13 May 2026 00:00:00 +0000</pubDate><guid>/en/posts/aihelper/hugo-theme-zhi-v11-upgrade/</guid><description>&lt;h2 id="one-month-in"&gt;One Month In&lt;/h2&gt;
&lt;p&gt;It&amp;rsquo;s been nearly a month since the previous article &lt;a href="/en/posts/aihelper/hugo-theme-zhi-intro/"&gt;Switched My Blog Theme: From Hugo NexT to Self-Written Zhi&lt;/a&gt;. During this month, the theme has been running stably without major issues. Replacing the NexT theme was the right decision — although there was some initial adjustment, the experience is now significantly better.&lt;/p&gt;
&lt;p&gt;After a month of use, the theme&amp;rsquo;s stability has exceeded expectations. My initial concerns — whether pure Hugo Pipes without build tools could support complex requirements — were proven unfounded. Daily maintenance has become very simple; modifying a feature no longer requires digging through deeply nested SCSS files — one CSS file gets the job done.&lt;/p&gt;</description></item><item><title>Evolution: Oh My OpenAgent Configuration Iteration Log</title><link>/en/posts/aihelper/oh-my-openagent-config-iteration/</link><pubDate>Thu, 07 May 2026 00:00:00 +0000</pubDate><guid>/en/posts/aihelper/oh-my-openagent-config-iteration/</guid><description>&lt;blockquote&gt;
&lt;p&gt;The previous article covered the initial configuration setup. This one documents the adjustments after two weeks of running: expanding from single vendor to a four-tier model pool, adding fallback chains, hitting the GLM-4.5-air trap of analyzing without writing code.&lt;/p&gt;
&lt;p&gt;This post covers: fallback strategy design, complete free model pool inventory and analysis, concurrency control configuration, and the decision process for GLM-4.5-air replacement.&lt;/p&gt;
&lt;/blockquote&gt;
&lt;p&gt;After the previous article&amp;rsquo;s initial configuration, I ran it for two weeks — all the issues that needed fixing surfaced.&lt;/p&gt;</description></item><item><title>Switched My Blog Theme: From Hugo NexT to Self-Written Zhi</title><link>/en/posts/aihelper/hugo-theme-zhi-intro/</link><pubDate>Thu, 16 Apr 2026 00:00:00 +0000</pubDate><guid>/en/posts/aihelper/hugo-theme-zhi-intro/</guid><description>&lt;h2 id="why-switch"&gt;Why Switch&lt;/h2&gt;
&lt;p&gt;This blog previously used &lt;a href="https://github.com/hugo-next/hugo-theme-next"&gt;Hugo NexT&lt;/a&gt;, forked for custom modifications. NexT itself is a feature-rich theme, but when it comes to &amp;ldquo;customizing things yourself,&amp;rdquo; the experience wasn&amp;rsquo;t great.&lt;/p&gt;
&lt;p&gt;The issues boiled down to a few things:&lt;/p&gt;
&lt;p&gt;&lt;strong&gt;SCSS nesting hell&lt;/strong&gt;. 101 SCSS files, three levels of directory nesting. &lt;code&gt;_common/components/post&lt;/code&gt;, &lt;code&gt;_common/components/third-party&lt;/code&gt;, &lt;code&gt;_common/outline/sidebar&lt;/code&gt;… To change a style, you first had to figure out which file it was in, where variables were defined, and which scheme was overriding it. Not that it couldn&amp;rsquo;t be done, but each change meant half an hour of hunting.&lt;/p&gt;</description></item><item><title>Zhipu Coding Plan × Oh My OpenCode: Multi-Model Orchestration Setup Guide</title><link>/en/posts/aihelper/zhipuai-coding-plan-oh-my-opencode-setup/</link><pubDate>Sun, 05 Apr 2026 00:00:00 +0000</pubDate><guid>/en/posts/aihelper/zhipuai-coding-plan-oh-my-opencode-setup/</guid><description>&lt;h2 id="why-bother"&gt;Why Bother&lt;/h2&gt;
&lt;p&gt;When it comes to writing code with AI, the gap between single-model and multi-model approaches keeps widening. No matter how strong a single model is, it can&amp;rsquo;t compete with a team of specialized models working in parallel.&lt;/p&gt;
&lt;p&gt;&lt;a href="https://github.com/code-yeongyu/oh-my-openagent"&gt;Oh My OpenCode&lt;/a&gt; (OmO for short) is a multi-model orchestration plugin in the OpenCode ecosystem, with 11 Agents each having distinct responsibilities and 48 Hooks spanning the entire lifecycle. &lt;a href="https://z.ai/subscribe"&gt;Zhipu&amp;rsquo;s Coding Plan&lt;/a&gt; provides access to the full GLM model series. Combining the two allows you to assign different models by role — strong coders for coding, strong reasoners for reasoning, free models for busywork.&lt;/p&gt;</description></item><item><title>Domestic LLM Resource and Cost Comparison: GLM-5 / Kimi K2.5 / MiniMax M2.7</title><link>/en/posts/aihelper/domestic-llm-cost-comparison/</link><pubDate>Mon, 23 Mar 2026 00:00:00 +0000</pubDate><guid>/en/posts/aihelper/domestic-llm-cost-comparison/</guid><description>&lt;h2 id="overview"&gt;Overview&lt;/h2&gt;
&lt;p&gt;This article compares the resource requirements and usage costs of three major domestic LLMs, helping developers choose the right solution for their scenarios.&lt;/p&gt;
&lt;table&gt;
	&lt;thead&gt;
			&lt;tr&gt;
					&lt;th&gt;Model&lt;/th&gt;
					&lt;th&gt;Vendor&lt;/th&gt;
					&lt;th&gt;Architecture&lt;/th&gt;
					&lt;th&gt;Minimum Deployable VRAM&lt;/th&gt;
					&lt;th&gt;API Available&lt;/th&gt;
			&lt;/tr&gt;
	&lt;/thead&gt;
	&lt;tbody&gt;
			&lt;tr&gt;
					&lt;td&gt;GLM-5&lt;/td&gt;
					&lt;td&gt;Zhipu AI&lt;/td&gt;
					&lt;td&gt;Dense (multiple versions)&lt;/td&gt;
					&lt;td&gt;24GB (8B)&lt;/td&gt;
					&lt;td&gt;✅&lt;/td&gt;
			&lt;/tr&gt;
			&lt;tr&gt;
					&lt;td&gt;Kimi K2.5&lt;/td&gt;
					&lt;td&gt;Moonshot AI&lt;/td&gt;
					&lt;td&gt;MoE (undisclosed)&lt;/td&gt;
					&lt;td&gt;24GB (lightweight)&lt;/td&gt;
					&lt;td&gt;✅&lt;/td&gt;
			&lt;/tr&gt;
			&lt;tr&gt;
					&lt;td&gt;MiniMax M2.7&lt;/td&gt;
					&lt;td&gt;MiniMax&lt;/td&gt;
					&lt;td&gt;MoE 230B&lt;/td&gt;
					&lt;td&gt;Not yet open-sourced&lt;/td&gt;
					&lt;td&gt;✅&lt;/td&gt;
			&lt;/tr&gt;
	&lt;/tbody&gt;
&lt;/table&gt;
&lt;h2 id="glm-5-zhipu-ai"&gt;GLM-5 (Zhipu AI)&lt;/h2&gt;
&lt;h3 id="versions--hardware-requirements"&gt;Versions &amp;amp; Hardware Requirements&lt;/h3&gt;
&lt;p&gt;GLM-5 offers 4 parameter versions, making it the widest-coverage domestic LLM currently available.&lt;/p&gt;</description></item></channel></rss>