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Self Media Content Analytics

Community
yanhua1010
self-media-content-analytics

分析单篇、系列、周度或月度自媒体数据并形成可执行复盘。用于读取平台后台截图、CSV、表格、公开链接或用户提供的数据,计算关注效率和深度互动,比较同平台基线,归因选题、标题、封面、开头、结构、发布时间、标签和行动,并输出加码、改包装、再适配、停止或继续收集样本的决策。

Overview

Publisheryanhua1010
Repositoryself-media-content-workflow
Skill nameself-media-content-analytics
Stars
584
Forks
80
Bundled files
6
LicenseMIT
Links
  • 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.

  • 6 bundled files

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

  • Open source

    Published by yanhua1010 on GitHub. Read the source before you install it.

Installation

Install the Self Media Content Analytics 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/yanhua1010/self-media-content-workflow/tree/main/skills/self-media-content-analytics
  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/yanhua1010/self-media-content-workflow.git /tmp/self-media-content-workflow
mkdir -p .claude/skills
cp -r /tmp/self-media-content-workflow/skills/self-media-content-analytics .claude/skills/self-media-content-analytics
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Self Media Content Analytics 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 Self Media Content Analytics 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 Self Media Content Analytics 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.

内容数据复盘

数据来源

优先使用:

  1. 用户提供的平台后台截图和导出文件。
  2. 已认证连接器或用户自有账号的只读统计接口。
  3. 内容任务卡、注册表和历史复盘。
  4. 公开内容链接,仅用于公开指标和结构观察。

不要估算平台没有提供的数据。读取自有账号数据不等于授权修改账号或发布内容。

需要持续记录时,从 metrics-ledger-template.md 创建原始指标台账。若项目已有数据库、表格或分析系统,继续使用现有系统,不重复建账。

分析流程

1. 校验数据

检查平台、内容、发布日期、观察窗口、字段定义、缺失值和异常值。区分曝光、阅读或播放、互动、关注、转化和制作成本。

2. 给出核心结论

说明表现相对自身基线如何、最值得注意的信号是什么,以及哪些结论不能成立。

3. 做归因

按证据强弱检查:

  • 选题和目标受众。
  • 标题和封面。
  • 开头 3 秒或第一屏。
  • 结构、证据和信息密度。
  • 发布时间、标签、合集和行动。
  • 热点、投流、商单和账号体量等外部因素。

相关性不等于因果。没有对照或样本不足时写“待验证”。

4. 做同类比较

只比较同平台、同内容类型和相近时间窗口。优先使用中位数、P75、每千浏览新关注、深度互动率和制作时间。跨平台原始播放量不能直接排名。

完整指标定义见 metrics.md。

5. 形成决策和实验

结论归入:加码、改包装、改主页或系列、平台再适配、停止、样本不足。

每次只设计一个主要实验变量,写清假设、改动、成功标准和观察窗口。

复盘层级

输出

交付:

  1. 核心结论。
  2. 数据质量和基线说明。
  3. 归因及证据强度。
  4. 可复制因素和不可归因因素。
  5. 3 到 5 条可执行动作。
  6. 待验证假设和唯一实验。

商单与自然内容分开分析。样本不足时不调整长期内容比例。

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 Self Media Content Analytics AI skill do?

分析单篇、系列、周度或月度自媒体数据并形成可执行复盘。用于读取平台后台截图、CSV、表格、公开链接或用户提供的数据,计算关注效率和深度互动,比较同平台基线,归因选题、标题、封面、开头、结构、发布时间、标签和行动,并输出加码、改包装、再适配、停止或继续收集样本的决策。

Why use Self Media Content Analytics on TypingMind?

Because you install it once and use it with any model. Self Media Content Analytics 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 Self Media Content Analytics in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/yanhua1010/self-media-content-workflow/tree/main/skills/self-media-content-analytics. 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 Self Media Content Analytics?

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 Self Media Content Analytics?

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

Is the Self Media Content Analytics AI skill free?

Yes. It is published on GitHub by yanhua1010 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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