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effect.video（及同模板站点）文章类页面的书写与上线流程：模型页 /models/<slug>、blog、模型对比、产品对比。 这不是通用写作 Skill，它把我们已定的分工（X 调研交 Grok、成文交 Gemini 3.8 Flash、review 交 Claude Sonnet、设计与实现交 Claude）、 资料采集规范（只拼别人的资料、来源可核实）、页面组件标准（YouTube iframe、X 评论墙、Prompt 集合卡、参数表/对比表、shadcn 图表、引导 card）、 以及最后的评判阶段（哥飞 AI 评分、AITDK 的 SEO/关键词密度/GEO 监测、ChatGPT 匿名问答）串在一起，并和 rankup、agent-fleet、write、gefei、opencli、design 联动。 只要任务是“写/改/迁移一篇站内文章或模型页”“给模型页补视频/评价/参数表”“写模型对比或产品对比文”“把页面内容写出来”，就用它；rankup 里凡是要写页面内容都引导到这里。 触发词：/blog、封面图、配图、文章封面、写文章、写 blog、model 页面、模型介绍页、模型对比、产品对比、seedance 文章、补参考视频、评论墙、X share card、文章标准化。

Overview

Publisheryan-labs
Repositoryyan-skills
Skill nameblog
Stars
225
Forks
94
Bundled files
7
LicenseMIT
Links
Skill sourceRepository
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 7 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by yan-labs on GitHub. Read the source before you install it.

Installation

Install the Blog AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/yan-labs/yan-skills/tree/main/blog
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/yan-labs/yan-skills.git /tmp/yan-skills
mkdir -p .claude/skills
cp -r /tmp/yan-skills/blog .claude/skills/blog
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Blog in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Blog on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Blog is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

blog · 我们自己的文章流程

这个 Skill 记录用户（2026-10-11）定下的文章类页面做法，只服务 effect.video 一类站点。它不重复别的 Skill 的内容，只规定“谁做什么、按什么顺序、哪些不许做”，细节指到对应 Skill 去读。

配图（封面图）与正文同等重要，是写文章的一部分：每篇文章都要有一张海报式封面，走 /imagegen，见 references/cover.md。

为什么这样做

文章的价值在可信：写的是别人已经说清楚的东西，我们负责挑选、衔接、梳理。自己编的数字、效果、评价一出错，就是 EEAT 的硬伤。所以流程把“找资料”和“写”拆开，资料先落成带出处的文件，写作模型只能用这个文件里的东西，再由另一个模型对着文件逐条核对。

一条铁律（其余规则都从它来）

不自编。 文章里每一个事实、数字、引文、评价都要能指回一条真实可访问的来源（sources/<slug>.json 里的一项）。我们自己的东西只有两类：衔接与梳理的话，以及站内计价/参数（由代码生成，不手写）。拿不到来源的内容宁可不写，写进报告“缺口”。

谁做什么

环节执行者说明
X 平台上的任何调研（找帖子、热点、社区评价、对比资料）Grok（fleet-go new … --to grok）帖子要带原始链接、作者、日期、是否含视频
YouTube 参考视频、Reddit、官方 blog/文档/定价Claude（fleet-go new … --to claude --tier sonnet，需浏览器时 opencli）官方与一手资料优先
画布设计（UI library 与“文章页标准”页）Claude（画布 agent，executor-sonnet；读写画布需本应用 Artifact 工具）先 UI library，后页面（见 /design）
组件/schema/深链接/数据源等架构决策Claude Opus复杂取舍
套用模板、页面迁移、机械编辑Claude Sonnet
成文Gemini 3.8 Flash（fleet-go new … --to gemini）把全部资料写进去，只做衔接与梳理，正面表述
成文后 reviewClaude Sonnet对着 sources 核对事实、引用、语气、夸大
代码/SEO 复核Claude Opus（只读）；Sol 只读也可maker 与 checker 不同人
封面图（每篇文章一张海报式封面）Codex image_gen（/imagegen，fleet-go new … --to gpt --make image）好莱坞大片感：夸张、强冲击力、视觉焦点鲜明；不出现文字/logo/商标/真实人物；详见 references/cover.md
部署与线上回读按 agent-fleet 的部署模板，生产只读回读生产不做真实付费验证

派单一律用 agent-fleet 的 fleet-go new（run_in_background，不加 &），写作 brief 模板见 references/writer-brief.md。

流程（一次做完，不往后排期）

每一步都有产物文件，写进 ~/.agent-reports/<日期>/ 并更新项目接力记录（rankup 的接力协议）。

  1. 摸底：当前路由/组件/schema/深链接/计价数据源（只读，Sol 或 Claude）。
  2. 画布：在同一张设计画布新建/更新“文章页标准”页，UI library 先定组件，再画 model 页、blog、模型对比、产品对比四种模板（/design，一页一页发布）。
  3. 组件实现：公共组件 + 内容 schema（向后兼容）+ /generator 按模型参数深链接 + X 嵌入 + shadcn 图表 + 参数表与积分图表数据由站内计价自动生成（frontmatter 只声明 model/xKind，不写数字）。URL、canonical 不变，JSON-LD 只增不改。草稿与 manifest 的 gaps 不进构建产物。详见 references/components.md。
  4. 资料采集：每篇文章一份 sources/<slug>.json，格式与来源规则见 references/sources.md。X 交 Grok，其余交 Claude。采集后逐条验证链接可打开、日期与作者对得上。
  5. 成文：Gemini 3.8 Flash 按 references/writer-brief.md 写；输入是 sources 文件、站内参数表数据、文章骨架。
  6. Review：Claude Sonnet 按 references/writer-brief.md 的清单核对，改动写回；通过后才进仓库。 6.5 封面图：每篇文章一张，按 references/cover.md 用 /imagegen 生成，落盘并转 webp，写进 frontmatter（cover、og 图同源）。
  7. 迁移与接入：写入 content/articles/**，页面三处引导 card（首屏、文中、文末），YouTube iframe 必备，X 评论墙，Reddit 仅链接，Prompt 集合卡（有则内置），参数表/对比表。
  8. 复核：Opus 只读复核代码与 SEO，Sonnet 复核内容；修必修项。
  9. 部署与回读：生产部署后只读回读（页面、嵌入可播放、JSON-LD、canonical、截图并排）；IndexNow。
  10. 评判：见 references/review-eval.md（哥飞 AI 评分、AITDK 监测、ChatGPT 匿名问答），分数不达标回到第 5 步。

页面必备件（模型页）

首屏（封面、标题、摘要、事实条、引导 card）→ 文章介绍 → YouTube 参考视频（宽屏 iframe，可全屏播放）→ 参数/价格表（入参出参、时长、每条与每秒积分）→ Prompt 集合卡（该模型有集合时）→ 社区评价墙（X share card，含可播放视频）+ Reddit 超链接 → 积分图表 → 文中引导 card → FAQ → 资料来源（官方文档/定价页在前，独立评测在后）→ 文末引导 card → 相关内链。引导 card 点击跳 /generator 并带模型参数。对比类文章把“参数表”换成“我们 vs 他们”的价格与功能表，竞品数据只引用有出处的采集。顺序与组件以 references/components.md 为准。

联动的 Skill

  • agent-fleet：派单与插话；rankup：接力记录、SEO/GEO 判据、评判阶段的脚本与清单。
  • write：中文稿的去 AI 味体检（站内英文稿不用）；gefei 系列：评分与关键词；opencli：登录态浏览器取数；design/画布：组件设计；imagegen：配图。
  • 评判标准与脚本都在 rankup，不要在这里复制一份。

做完怎么交

报告给：每篇文章的 sources 条数与类型、缺口、Gemini 初稿与 Sonnet review 的改动摘要、评判分数、线上回读证据。没验证的写“未验证”。

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Blog AI skill do?

effect.video（及同模板站点）文章类页面的书写与上线流程：模型页 /models/<slug>、blog、模型对比、产品对比。 这不是通用写作 Skill，它把我们已定的分工（X 调研交 Grok、成文交 Gemini 3.8 Flash、review 交 Claude Sonnet、设计与实现交 Claude）、 资料采集规范（只拼别人的资料、来源可核实）、页面组件标准（YouTube iframe、X 评论墙、Prompt 集合卡、参数表/对比表、shadcn 图表、引导 card）、 以及最后的评判阶段（哥飞 AI 评分、AITDK 的 SEO/关键词密度/GEO 监测、ChatGPT 匿名问答）串在一起，并和 rankup、agent-fleet、write、gefei、opencli、design 联动。 只要任务是“写/改/迁移一篇站内文章或模型页”“给模型页补视频/评价/参数表”“写模型对比或产品对比文”“把页面内容写出来”，就用它；rankup 里凡是要写页面内容都引导到这里。 触发词：/blog、封面图、配图、文章封面、写文章、写 blog、model 页面、模型介绍页、模型对比、产品对比、seedance 文章、补参考视频、评论墙、X share card、文章标准化。

Why use Blog on TypingMind?

Because you install it once and use it with any model. Blog is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Blog in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/yan-labs/yan-skills/tree/main/blog. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Blog?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Blog?

As many as you like. As long as a model supports skills, you can use Blog with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Blog AI skill free?

Yes. It is published on GitHub by yan-labs under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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