grill-me

Probe plans with one question per turn to uncover assumptions and missing decisions.

8|1|Updated Feb 22, 2026
One-click install
npx skills add https://github.com/ccomkhj/skills --skill grill-me-ccomkhj
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: grill-me
Source: https://github.com/ccomkhj/skills/tree/main/grill-me
Command: npx skills add https://github.com/ccomkhj/skills --skill grill-me-ccomkhj

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

It helps you stress-test a plan, design, or data-related product by uncovering hidden assumptions, missing decisions, weak logic, and unexamined risks before you invest heavily.

Core Features & Use Cases

  • One-question-at-a-time grilling: forces clarity in small increments so you don’t skip over uncertainty.
  • Assumption and risk probing: targets unclear users, success criteria gaps, hidden dependencies, data quality risks, trust/explainability gaps, and failure modes.
  • Reconciliation of vague or conflicting answers: requires the next question to quote vague/conflicting phrases until you align.

Quick Start

Ask the assistant to grill you on your plan by asking you the first question using the required Q/Why it matters/Recommended answer template.

Frequently Asked Questions about grill-me

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I test product planning assumptions before building?

Stress-testing a plan involves probing unclear users, success criteria gaps, hidden dependencies, and data quality risks through a guided one-question-at-a-time interrogation framework.

How do I uncover hidden risks in a data product design?

You apply assumption testing to target data quality risks, identify decisions made from outputs, and probe edge cases or privacy concerns to reconcile vague or conflicting answers.

What is the best way to stress-test a product plan?

This one-question-at-a-time grilling approach forces clarity in small increments so you do not skip over uncertainty, requiring you to quote vague phrases until aligned.

Can I use assumption testing for data quality and privacy concerns?

The grilling process explicitly targets data quality risks, trust and explainability gaps, and privacy or permission concerns to ensure your data outputs are robust.

How do I reconcile vague or conflicting answers during risk discovery?

By forcing you to quote vague or conflicting phrases from previous answers, the process ensures you resolve logical contradictions and align on decisions incrementally.

When do I need assumption testing for product validation?

Apply this technique before investing heavily in a data initiative, design, or product plan to identify missing decisions, weak logic, and hidden assumptions early.