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grill-me — AI agent skill | AgentStack

Skills/Business Ops/grill-me

Skill Indexed source

grill-me

pietdaniel/workstation-setup

Open source

Popularity

Forks

—

Quality

In review

Freshness

Synced today

What it does

Built for Business Ops workflows.

An AI tool that rigorously interviews users about their plans or designs to ensure thorough understanding and decision resolution.

Skill profile

Use this skill when

Your agent needs help with business ops workflow.
You want reusable instructions rather than recreating a workflow from scratch.
You have reviewed the source and want to add this capability to a supported agent.

Keep exploring

Recommended skills

More options in Business Ops.

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Agent compatibility

Claude Code · Codex · OpenClaw

Repository language

Python

Source activity

Updated 7/23/2026

Agent compatibility

Compatibility has not been reviewed for this listing yet. Check the publisher documentation before installing.

Installation

Install this skill

npx skills add https://github.com/pietdaniel/workstation-setup --skill grill-me

Review source code and installation permissions before adding third-party tools to an agent.

Best fit

grill-me is organized in the Business Ops category. Compare its source, install method, and compatibility before adding it to your workflow.

Before you install

Third-party agent tools may access source code, credentials, or browser sessions. Read the source documentation and use the minimum permissions needed.

Available install methods

Quick installnpx skills add https://github.com/pietdaniel/workstation-setup --skill grill-me

SKILL.md

---
name: grill-me
description: Interview the user relentlessly about a plan or design until reaching shared understanding, resolving each branch of the decision tree. Use when user wants to stress-test a plan, get grilled on their design, or mentions "grill me".
---

Interview me relentlessly about every aspect of this plan until we reach a shared understanding. Walk down each branch of the design tree, resolving dependencies between decisions one-by-one. For each question, provide your recommended answer.

Ask the questions one at a time.

If a question can be answered by exploring the codebase, explore the codebase instead.

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