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Grill Me

Community
JasonxzWen
grill-me

Load when beginning every repository mutation task to run one dependency-layered batch interview; a fully aligned task takes the zero-question path, while durable documentation work uses grill-with-docs to reuse the same decision graph.

Overview

PublisherJasonxzWen
Repositoryharness-hub
Skill namegrill-me
Stars
71
Forks
0
Bundled files
Instructions only
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.

  • Self-contained

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

  • Open source

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

Installation

Install the Grill Me 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.
  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/JasonxzWen/harness-hub.git /tmp/harness-hub
mkdir -p .claude/skills
cp -r /tmp/harness-hub/skills/grill-me .claude/skills/grill-me
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable 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.

The model loads Grill Me 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 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.

  • 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.

Grill Me

Purpose

Run one compact alignment pass before changing a repository. Surface only unresolved decisions that can change the work, arrange them by dependency, and minimize user interruption.

This is an atomic prompt capability for the native Host main Agent. It is not a workflow owner, implementation phase, state machine, or permission grant.

Activation

Run once per mutation task, not once per file, edit, or tool call.

If the task creates or materially changes durable project contracts, OKF knowledge, specifications, ADRs, architecture/API/design documents, load grill-with-docs; it loads and applies this protocol through one shared graph, so do not conduct a second interview. Temporary .harness-hub/state/ maintenance alone does not qualify.

Explicit grill me requests still use this skill. Read-only explanation or status work does not require it unless it turns into a mutation task.

Alignment Protocol

  1. Restate the intended outcome, allowed scope, non-goals, and acceptance evidence.
  2. If a fact can be learned locally, inspect the repository first instead of asking the user.
  3. Separate facts, accepted decisions, reasonable reversible assumptions, and unresolved decisions.
  4. Ask only about decisions that can change behavior, ownership, safety, material cost, remote state, or acceptance criteria.
  5. Build a lightweight dependency graph for those unresolved decisions.
  6. Ask every unresolved decision whose complete row—question, options, recommendation, rationale, tradeoff, and downstream impact—can be stated without another open answer.
  7. Defer a decision when any part of that row depends on an unresolved answer.
  8. Apply the user's answers, prune invalid branches, recompute the current frontier, and repeat only while a consequential decision remains.

If no unresolved decision can change the next action, ask zero questions, state that alignment is complete, and continue with the user's authorized work.

Never infer that silence means acceptance. Facts are for the Agent to investigate; decisions with meaningful user-visible consequences remain with the user.

Batch Format

Present the current dependency frontier in one table:

IDDecision questionOptionsRecommendedWhy / tradeoffDownstream impactAnswer
D1A decision that is answerable nowA / B / CAWhy A is the best default and its costWhat this unlocks, constrains, or prunesPending

Every row must include a recommended default, short rationale, main tradeoff, and likely downstream consequence. Keep options mutually exclusive. Do not impose an arbitrary batch-size cap. Group a large frontier by theme or priority without serializing independent questions across turns.

Show dependency-bound topics only as a waiting list:

Deferred topicPrerequisiteWhy it waits
Cache authorityD1 source choiceValid options depend on the authoritative source

Do not finalize the wording or options for a deferred question until its prerequisite is resolved.

Invite one compact reply, for example:

text
D1: choose A
D2: accept recommendation
D3: pause until <condition>

The user may say accept this batch, answer in prose, or use default, defaults, and defer. Do not silently apply a recommendation to an unanswered row.

Treat pause until ... as an explicit deferral. Record its reason and re-entry condition, and omit it from later batches until that condition becomes true or the user explicitly reopens it. The same lifecycle applies to the defer alias.

After each reply, show only the useful resolution summary:

IDDecisionConsequenceStatus
D1Accepted choiceWhat it resolved, unlocked, or prunedResolved

Batching is the default. If the user explicitly asks for one question at a time, honor that request without changing the dependency or evidence rules.

Boundaries And Handoff

  • Do not ask vague preference questions when repository evidence or a reversible default is enough.
  • Do not create a run ledger, retry counter, workflow, hook, or hidden state.
  • Do not expand authorization. Remote writes, destructive work, security boundaries, and data ownership still require their normal authority.
  • Do not start implementation unless the user explicitly asks you to continue into execution.

When stopping, return decisions made, assumptions used, deferred questions and their prerequisites, the next authorized action, and verification criteria for the next step.

Frequently asked questions

What does the Grill Me AI skill do?

Load when beginning every repository mutation task to run one dependency-layered batch interview; a fully aligned task takes the zero-question path, while durable documentation work uses grill-with-docs to reuse the same decision graph.

Why use Grill Me on TypingMind?

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.

How do I install Grill Me in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/JasonxzWen/harness-hub/tree/main/skills/grill-me. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Grill Me?

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 Me?

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.

Is the Grill Me AI skill free?

Yes. It is published on GitHub by JasonxzWen 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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