对用户的计划或设计进行不留情面的深度追问，直到达成共同理解，逐一解决决策树的每个分支。当用户想要压力测试计划、检验设计时触发。触发词：追问我、grill me、逐一问我、挑战我的方案、深度追问、质疑设计、设计评审追问。
| Publisher | ProgrammerAnthony |
| Repository | Expert-Coding-Harness |
| Skill name | grill-me |
| Stars | 236 |
| Forks | 77 |
| Bundled files | Instructions only |
| License | MIT |
| Links |
A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.
AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.
Everything the model needs lives in the instructions — no extra files to sync.
Published by ProgrammerAnthony on GitHub. Read the source before you install it.
Install the Grill Me AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.
TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.
Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.
git clone --depth 1 https://github.com/ProgrammerAnthony/Expert-Coding-Harness.git /tmp/Expert-Coding-Harness
mkdir -p .claude/skills
cp -r /tmp/Expert-Coding-Harness/skills/grill-me .claude/skills/grill-meEnable Grill Me 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.
AI skills are plain Markdown instructions rather than provider-specific code, so Grill Me 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.
The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.
Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.
This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.
对我的计划的每个方面进行不留情面的追问，直到我们达成共同理解。逐一解决决策树的每个分支，按依赖关系顺序推进。对每个问题，提供你推荐的答案。
每次只问一个问题，等待我对当前问题的反馈后再继续。
如果某个问题可以通过探索代码库来回答，直接探索代码库而不是问我。
对用户的计划或设计进行不留情面的深度追问，直到达成共同理解，逐一解决决策树的每个分支。当用户想要压力测试计划、检验设计时触发。触发词：追问我、grill me、逐一问我、挑战我的方案、深度追问、质疑设计、设计评审追问。
Because you install it once and use it with any model. Grill Me 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.
Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/ProgrammerAnthony/Expert-Coding-Harness/tree/master/skills/grill-me. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.
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.
As many as you like. As long as a model supports skills, you can use Grill Me with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.
Yes. It is published on GitHub by ProgrammerAnthony under the MIT license. You only pay your own AI provider for the tokens you use.
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.
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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