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Grill Me

Community
Dianel555
grill-me

Grill the user about a requirement, decision, or idea before implementation, then produce an actionable planning report without writing code. Use when the user wants to clarify requirements, stress-test an idea, compare approaches, or plan before coding.

Overview

PublisherDianel555
RepositoryDSkills
Skill namegrill-me
Stars
65
Forks
8
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 Dianel555 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.
    https://github.com/Dianel555/DSkills/tree/main/skills/grill-me
  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/Dianel555/DSkills.git /tmp/DSkills
mkdir -p .claude/skills
cp -r /tmp/DSkills/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

Turn an incomplete idea into an evidence-backed, actionable plan. Scale the depth to the work without adding unnecessary process.

Boundaries

  • Perform discovery, clarification, option analysis, and planning only.
  • Do not write code, patches, or pseudocode; modify project files; install dependencies; or run commands with side effects.
  • Do not invoke or depend on OC, OpenSpec, or their workflows.
  • Facts are the agent's responsibility; material decisions belong to the user.
  • Use read-only tools to inspect relevant code, configuration, and documentation. Use independent agents only when separate context boundaries materially reduce uncertainty.
  • Deliver the planning report, then stop and wait for a separate implementation request.

Adaptive Depth

Scale depth, not ceremony:

  • Lightweight: For narrow, reversible, low-risk work, inspect only direct context, ask no questions when the input is sufficient, target zero to two rounds, and keep the report concise.
  • Medium: For multi-module changes or integrations, cover boundaries, interfaces, data flow, failure behavior, dependencies, compatibility, testing, and rollback where relevant.
  • Large or high-risk: For broad blast radius, migrations, sensitive data, or critical availability, define workstreams, contracts, milestones, rollout gates, observability, and recovery. Prefer an honest framework over false precision, and mark unresolved readiness gates explicitly.

Remain planning-only at every depth; do not silently switch workflows.

Process

1. Frame and Investigate

Extract the desired outcome, target users, current state, deliverable, scope, non-goals, constraints, and observable acceptance criteria.

Investigate facts that can change the plan. Cite repository paths, configuration, documentation, or external sources when they support a conclusion, and distinguish verified facts from assumptions.

Cover only relevant planning dimensions:

  • User flows, expected behavior, edge cases, and failure states
  • Architecture, conventions, integrations, interfaces, data ownership, and migration
  • Security, privacy, reliability, performance, accessibility, and compatibility
  • Dependencies, rollout, rollback, observability, support, and maintenance

If the available information is sufficient, skip the interview and produce the report.

2. Build the Decision Tree

Model each material decision with its prerequisites, viable options, recommended answer, rationale, and downstream consequences.

The frontier is every unresolved decision whose prerequisites are settled. Questions depending on unresolved answers belong to a later round. Discoverable facts are not user questions; low-impact preferences receive a safe conventional default recorded as an assumption.

3. Work in Rounds

Ask the complete currently answerable frontier, number every question, and include a clear recommendation with a short reason. Then wait for the user's answers.

Use Pi's structured question tool for at most four closed-choice questions; otherwise use numbered text. If a fact lookup is pending, delay only the questions that depend on it and ask the rest of the frontier now.

After each response, update settled decisions, recompute the tree and frontier, investigate newly required facts, and ask only newly unblocked material questions.

If the user says "you decide," accepts the recommendations, or requests a one-shot result, adopt the recommended options and record them as delegated decisions or assumptions.

4. Select and Sequence the Solution

Compare viable approaches using the relevant criteria: goal fit, simplicity, consistency with the existing system, effort, compatibility, reversibility, operational risk, and maintainability.

Choose one recommended approach. Keep alternatives only when they represent a meaningful trade-off or fallback.

For every implementation step, name the intended outcome, affected boundary when known, prerequisites, concrete deliverable, and verification method. For larger work, group steps into ordered milestones or workstreams and state cross-boundary dependencies.

5. Close the Loop

Finish when goals, scope, non-goals, acceptance criteria, material decisions, relevant functional and non-functional requirements, dependencies, risks, and validation are actionable. Record every remaining unknown; do not continue merely to eliminate harmless uncertainty.

Assign one status:

  • Ready: no unresolved blocker prevents implementation.
  • Conditional: implementation depends on named assumptions or gates.
  • Blocked: a critical fact or decision is missing; identify how to resolve it.

Planning Report

Adapt the length to the request. Merge sections for lightweight work and include operational detail only when relevant; never pad the report with empty boilerplate.

markdown
# Planning Report: <topic>

**Status:** Ready | Conditional | Blocked

## Executive Recommendation
<Recommended approach, reason, expected result, and primary trade-off.>

## 1. Goal and Scope
- Users and desired outcome:
- Current state and constraints:
- In scope / out of scope:
- Acceptance criteria:

## 2. Evidence and Requirements
- Verified facts and sources:
- Functional requirements:
- Relevant non-functional requirements, edge cases, and failure behavior:

## 3. Decisions and Options
- <Decision>: <selection and rationale>
- Alternatives: <meaningful rejected or fallback options>

## 4. Proposed Solution and Impact
- Solution outline:
- Affected boundaries, interfaces, data, and dependencies:

## 5. Execution Plan
1. <Step> -> Outcome: <result> -> Deliverable: <artifact> -> Verification: <check>
2. ...

For larger work, organize steps into ordered milestones or workstreams and identify cross-workstream dependencies.

## 6. Validation and Delivery
- Test and acceptance evidence:
- Migration, rollout, observability, rollback, and recovery when relevant:

## 7. Risks and Open Items
- Risks and mitigations:
- Assumptions:
- Remaining decisions or readiness gates:

## 8. Next Action
<The smallest concrete action that moves the plan forward.>

Before returning the report, verify that goals trace to requirements, planned work, and acceptance evidence; recommendations are grounded in facts or explicit assumptions; every step has an output and verification method; no blocker is hidden; and no implementation code or speculative architecture was added.

Frequently asked questions

What does the Grill Me AI skill do?

Grill the user about a requirement, decision, or idea before implementation, then produce an actionable planning report without writing code. Use when the user wants to clarify requirements, stress-test an idea, compare approaches, or plan before coding.

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/Dianel555/DSkills/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 Dianel555 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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