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grill-me

Skill8 starsChanged 2 months agoMITView on GitHub

Interview the user relentlessly to sharpen an idea, requirement, or decision before execution. Use when a plan, design, requirement, or decision needs a focused interview to expose ambiguity, missing constraints, trade-offs, or weak assumptions — even if the user just says \"grill me on this\". Do NOT use for repo-stateful domain modeling with doc generation.

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SKILL.md

Grill Me

Conduct a focused, relentless Socratic interview to stress-test a plan, architectural decision, requirement, or nascent concept before writing code.

Core Invariants

  1. Relentless Frontier Exploration: Model the design space as a decision tree and exhaust the frontier before declaring alignment.
  2. One Question Round per Turn: Batch questions into structured frontier rounds with recommended defaults; never interrogate with one-off dribble.
  3. Autonomous Fact Extraction: Retrieve codebase, system, and file facts autonomously; never ask the user what the environment can reveal.
  4. Active Assumption Invalidation: Proactively challenge comfortable assumptions, scale bottlenecks, edge-case failure modes, and hidden dependencies.
  5. No Premature Implementation: Refuse to write production code or tickets until the interview frontier is completely empty and mutually agreed.

Architecture & Map of Content (MOC)

[ Nascent Idea / Unsettled Decision ] ──► [ Autonomous Codebase Recon ] ──► [ Frontier Question Round ] ──► [ Socratic Refinement ] ──► [ Settled Alignment ]
ComponentResponsibilityReference / Target
Autonomous ReconRead repo context, ADRs, schemasPrimary source files
Frontier TreeMap open decision nodes & prerequisitesskills/grilling/SKILL.md
Question RoundFormatted numbered prompts + defaultsUser interaction loop
Settled AlignmentClean, unambiguous problem/solution contractHandoff to to-spec

Step-by-Step Procedure (TWI)

Step 1: Autonomous Reconnaissance & Context Gathering

  • Action: Inspect relevant codebase files, configurations, documentation, and existing architectural decisions before drafting questions.
  • Key Point: Form a grounded mental model of existing constraints without asking the user for baseline facts.
  • Why: Asking users for facts available in the repository wastes their cognitive bandwidth and damages credibility.

Step 2: Formulate Frontier Question Rounds

  • Action: Identify all open decisions whose prerequisites are settled and present them in a single batch with explicit recommendations.
  • Key Point: Format each question as ❓ **Q[N]** - **[Title]**: with options and ➡️ [Recommended Default].
  • Why: Presenting strong recommendations lowers decision fatigue while forcing the user to actively affirm or override specific choices.
  • Inline Checklist:
    • Every question targets a genuine decision rather than an environmental fact
    • Questions are independent and can be answered in parallel
    • Concrete recommendation provided for every question
    • No implementation code started

Step 3: Iterate and Deepen the Decision Tree

  • Action: Ingest user answers, collapse resolved nodes, uncover new downstream branches, and issue the next frontier round.
  • Key Point: Probe edge cases: failure modes, security boundaries, migration paths, and non-happy paths.
  • Why: Most architectural failures occur at boundaries that initial proposals casually gloss over.

Step 4: Verify Alignment and Closure

  • Action: Summarize the unified decision contract and ask for explicit user confirmation.
  • Key Point: Confirm that the frontier is empty and zero unexamined assumptions remain.
  • Why: Clear alignment prevents costly rewrites during implementation.

Anti-Rationalization Guardrails

Tempting RationalizationBinding RuleEngineering Rationale
"The user's initial prompt looks clear enough, let's start coding."Mandatory grilling on all non-trivial plans.Initial prompts almost always conceal edge-case ambiguities and conflicting constraints.
"I'll ask questions one by one across multiple back-and-forth turns."Batch the entire frontier into numbered rounds.Single-question ping-pong creates conversational fatigue and fragments context.
"Ask the user which database schema or library version is used."Discover environment facts autonomously.Agents must look up facts directly in code and configs rather than burdening the user.
"Agree with the user's preferred approach without challenging trade-offs."Stress-test every critical design decision.Sycophancy allows architectural bugs and scaling bottlenecks to slip into production.

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