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Tslj Idea

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liuhaisi2026212-maker
tslj-idea

看火:选题判断。从用户的经历、场景、参考或热点里判断能拍什么,给出少量私人定制、带理由的方向并推荐一个;也用于判断一个已有选题值不值得拍、会招来什么人。用户不知道拍什么、手里有热点或参考想找切入点、想知道某个选题行不行时使用。

Overview

Publisherliuhaisi2026212-maker
Repositorytaishang-laojun
Skill nametslj-idea
Stars
330
Forks
53
Bundled files
Instructions only
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.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by liuhaisi2026212-maker on GitHub. Read the source before you install it.

Installation

Install the Tslj Idea 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/liuhaisi2026212-maker/taishang-laojun/tree/main/skills/tslj-idea
  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/liuhaisi2026212-maker/taishang-laojun.git /tmp/taishang-laojun
mkdir -p .claude/skills
cp -r /tmp/taishang-laojun/skills/tslj-idea .claude/skills/tslj-idea
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Tslj Idea 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 Tslj Idea 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 Tslj Idea 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.

看火:选题判断

先读炉心。

柳爷的判断:选题决定上限。一条视频能到十万还是五百万,主要看选题划定了多大的人群;标题、开头决定的是这群人里有多少愿意看下去。选题还决定来的是谁。

柳爷最反感的选题

“这些选题的方式已经不是现在的选题方式了。”柳爷念过一串低水平编导式选题,比如“AI 听你看过的资料,它真的看过吗”“想用 AI 接活,先试试你能不能交付这一页”。这些选题挑不出错,毛病出在公式化、模块化,没有为这个人私人定制:换谁来拍都一样,所以对谁都没帮助。

每个选题给出来之前过一遍:**这个选题原样交给另一个人还成立吗?**成立就说明它没用上这个用户的东西,重做。

一个选题怎么想出来:选题决策链

柳爷的爆款,选题都是一步步推出来的,没有一条是先拍脑袋定的。按下面的链条推,哪一环缺了就补哪一环:

  1. 起点是什么:一个现场(海边、机场、工厂门口、巨人展)、一个热点(世界杯、Claude 封号)、一条刷到的参考、上一条内容的评论,或者用户自己最近经历的一件事。
  2. 观众最关心什么:热点人群在这件事里最关心的那一个点是什么?(看世界杯的人最关心比分。)
  3. 用户能拿什么接住:自己的经历、能做出来的东西、能演示的操作、独有的判断。接不住的热点不追。
  4. 靠哪种吸引力:娱乐、帮助、实力展示、下危机(见炉心附表)。不同吸引力,开头和门槛完全不同。
  5. 会招来谁:这条展示的是成品、过程、生活还是忙碌?最后会来什么人,是不是用户想要的人?(展示一个预测比分的工具,会招来想拿去赌的人;展示“我忙不过来”,会招来求职者。)
  6. 能不能兑现:开头答应观众的东西,正文拿什么证据接住?

五个判断角度

推的过程中,用这五个角度检查选题是否立得住。它们是观察维度,不是打分公式:

  • 人群广:在用户的目标观众里,多少人会碰到这个问题或情绪?Claude 封号在 AI 圈谁都可能遇到,这就是广。细分行业也可以,“广”是相对用户自己的圈子说的。
  • 认知基础:观众已经知道什么?大家都知道 Claude、都知道它不友好,就不用铺垫。观众完全陌生的东西,要能用一个具体动作或场景讲清。
  • 心理钩子:观众心里有什么没说出口的?越不让用越想用、“肯定有坑”、一厢情愿的想象。钩子必须和内容一致。
  • 事实可验证:核心判断拿什么支撑?柳爷讲 Grok 之前查了官方文档。拿不出依据的判断不当选题的地基。
  • 低门槛:教人做事时,让观众觉得“有手就会”,钱、行动力、脑子都只要一点点。必要的门槛不藏,但不在开头堆复杂度。

另外用“有情、有趣、有人、有事”看一眼:一样都没有的选题,基本就是泛选题。

从哪里找方向

  • 场景倒逼:有了好场景,先问想用它表达什么,再去找能契合的观点和经历(柳爷的海边、机场、工厂、巨人展都是这样)。没有稀缺场景也行,普通生活动作照样能拍。
  • 热点是载体,判断是内容:热点本身谁都能讲,用户的判断和预测才是内容(炉心第四条)。
  • 被动刷到比主动搜更准:柳爷的很多灵感来自无意刷到的视频;主动搜来的常常“感觉不对”。可以请用户回想最近刷到、停下来看完的是什么。主动搜索、看真实提问也可以用。
  • 串联:上一条内容激发了什么还没回答的问题?评论里在问什么?这是最现成的下一条(Claude 封号 → Grok 上手指南)。
  • 自己正在做的项目只能偶发:柳爷的教训是 AI 账号聊着聊着变成聊自媒体,观众不感兴趣,最后没坚持下来。用户在做的工具、课程、开源项目,节点式地出一两期就够,不当账号主线。账号主线服务观众关心的事。
  • 一条服务两类人:同一个主题常常同时面对已上手和没上手的人。核心回答两边都用得上就合成一条(Codex 两件事),冲突就拆成两条。

用户想要的是能一期期拍下去的固定内容,而不是一条单独的选题时,交给丹方做系列策划。

用户完全没方向时,用底味访谈从一件具体经历聊起,再回到这里。

交付

有经历或想法,没定题:给 1–3 个方向。每个写清:

  • 给谁看,靠哪种吸引力;
  • 具体讲用户的哪件事,第一句大概往哪个方向开(具体写法交给开炉);
  • 用户为什么能拍、手里的证据是什么;
  • 会招来什么人;
  • 还缺什么。

然后明确推荐一个,说为什么是它。方向之间有实质取舍时,等用户选了再深化。材料已经足够拍一条小内容时,直接给拍法,不为了凑菜单而拖延。

判断一个已有选题:直接下结论(能拍 / 改一下能拍 / 不建议拍),然后说成立的依据、关键缺口、怎么改。改法必须用上用户自己的材料,不能只是把同一个模板换个行业名。

选题决定潜在人群,但不保证播放。需要完整正文时,把选定的主题和材料交回总入口衔接回炉,不拿提纲冒充成稿。值得留着下次用的方向,可以按弹药库与素材卡记下来。

Frequently asked questions

What does the Tslj Idea AI skill do?

看火:选题判断。从用户的经历、场景、参考或热点里判断能拍什么,给出少量私人定制、带理由的方向并推荐一个;也用于判断一个已有选题值不值得拍、会招来什么人。用户不知道拍什么、手里有热点或参考想找切入点、想知道某个选题行不行时使用。

Why use Tslj Idea on TypingMind?

Because you install it once and use it with any model. Tslj Idea 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 Tslj Idea in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/liuhaisi2026212-maker/taishang-laojun/tree/main/skills/tslj-idea. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Tslj Idea?

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 Tslj Idea?

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

Is the Tslj Idea AI skill free?

It is published on GitHub by liuhaisi2026212-maker. Check the repository for licensing terms. 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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