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Grill

Organization
nagi-studio
grill

分轮追问用户的计划、决定或想法,直到重要未知暴露出来,再动手执行。适用于任何领域,不限于写代码。当用户想理清思路、给想法做压力测试,或者说出这些话时使用:拷打我、追问我、帮我想清楚、帮我理一理、挑挑毛病、有什么没想到的、grill me、stress-test this、poke holes in this、interview me。

Overview

Publishernagi-studio
Repositoryskills
Skill namegrill
Stars
277
Forks
3
Bundled files
1
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.

  • 1 bundled files

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

  • Open source

    Published by nagi-studio on GitHub. Read the source before you install it.

Installation

Install the Grill 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/nagi-studio/skills/tree/main/skills/pondering/grill
  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/nagi-studio/skills.git /tmp/skills
mkdir -p .claude/skills
cp -r /tmp/skills/skills/pondering/grill .claude/skills/grill
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Grill 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 Grill 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 Grill 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.

先问拷打强度,以及要不要留决策记录(decision log)。用户已说明的不再问。

  1. 浅问:只补最关键的缺口
  2. 常规:把明显没想清楚的地方问明白
  3. 细问:检查目标、约束、取舍和默认假设
  4. 深挖:主动寻找风险、遗漏和边界情况
  5. 拷打:严格挑战前提,直到重要未知基本暴露

用户可以随时调整强度。

要留记录时,每定一条就追加「结论 + 理由」,另列待定问题。能写文件就新建 docs/decisions-<英文主题>.md;不能就每隔几轮贴出完整版供复制。

分轮进行。每轮询问当前已经具备前提的问题,可以是一条,也可以是多条。依赖尚未确定答案的问题,留到下一轮。

优先追问会明显影响后续方案的内容:

  • 真正想解决什么问题
  • 哪些事情已经确定
  • 哪些事情还没有决定
  • 哪些前提只是用户默认成立
  • 有没有用户尚未意识到的重要问题
  • 哪些取舍会改变后续方向

能自己查清楚的事实不要交给用户;涉及用户的目标、偏好、成本和取舍时,再让用户决定。必要时提供选项和建议,但不要替用户决定。

每个问题使用:

❓ Q1|问题标题
问题内容。需要时给出选项。
➡️ 建议:简短给出你的推荐和理由。

同一轮有多个问题时继续 Q2、Q3。问题保持具体、容易回答。不要一次堆出大量低价值问题。

强度决定追问深度,不只是问题数量:

  • 浅问只处理会卡住下一步的问题。
  • 常规补齐明显缺口。
  • 细问开始检查隐含假设和重要取舍。
  • 深挖主动寻找边界情况、风险和遗漏。
  • 拷打会挑战模糊回答、未经验证的前提和互相冲突的要求。

不要为了「拷打」而无限追问。当剩余未知已经不足以明显改变下一步时停止。

最后简短总结:

  • 已确定
  • 暂未确定
  • 下一步

等待用户确认后再开始重要执行。

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 Grill AI skill do?

分轮追问用户的计划、决定或想法,直到重要未知暴露出来,再动手执行。适用于任何领域,不限于写代码。当用户想理清思路、给想法做压力测试,或者说出这些话时使用:拷打我、追问我、帮我想清楚、帮我理一理、挑挑毛病、有什么没想到的、grill me、stress-test this、poke holes in this、interview me。

Why use Grill on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/nagi-studio/skills/tree/main/skills/pondering/grill. 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 Grill?

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 Grill?

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

Is the Grill AI skill free?

Yes. It is published on GitHub by nagi-studio 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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