agentleFS
imMamdouhaboammarimMamdouhaboammar/matts-skills-into-chatgpt/skills/grilling/SKILL.md

grilling

Skill8 starsChanged 2 months agoMITView on GitHub

Relentlessly interview the user round-by-round to stress-test thinking and expose unexamined assumptions. Use when the user requests a grilling interview, wants their idea challenged, or uses trigger phrases like \"grill me\" — even if they just say \"poke holes in my plan\". Do NOT use when the user asks for immediate implementation.

We split this skill into the rules it gives an agent

4 rules. 0 are common, 3 are distinctive, and 1 is very specific to this project.

  • 0

    Common

    Most of the 76 edited versions we read keep these.

  • 3

    Distinctive

    This author's own choices. Worth a look.

  • 1

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Frontier-Based Batched Rounds: Ask all currently unblocked questions together in a single numbered round.

    line 14
  2. Very specific:

    Mandatory Concrete Recommendations: Every question must include a definitive recommended answer (➡️ [Recommendation]) to streamline …

    line 15
  3. Distinctive:

    Key Point: Keep recommendations opinionated, clear, and grounded in industry best practices.

    line 80
  4. Distinctive:

    Key Point: If a user response reveals a new unknown in the codebase, dispatch background exploration immediately to resolve it.

    line 88

“Common” is measured: kept by at least 6 in 10 of the 76 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Grilling

Relentlessly stress-test thinking, expose hidden assumptions, and map the design space as an expanding decision tree until mutual understanding is reached.


Core Invariants

  1. Frontier-Based Batched Rounds: Ask all currently unblocked questions together in a single numbered round; never drip questions one by one.
  2. Mandatory Concrete Recommendations: Every question must include a definitive recommended answer (➡️ [Recommendation]) to streamline decision-making.
  3. Autonomous Fact Exploration: Investigate the codebase, configs, and dependencies with background exploration before asking questions; never query the user for discoverable facts.
  4. Strict Topological Dependency Ordering: Questions whose answers depend on open decisions must wait for future rounds; never mix dependent questions into the current frontier.
  5. Verified Exhaustion Gate: The interview concludes only when the frontier is completely empty and the user explicitly validates the final consensus.

Architecture & Map of Content (MOC)

[ Problem Space / Initial Proposal ]
                │
                ▼
┌───────────────────────────────────────┐
│ 1. Compute Decision Frontier Tree     │
│    (Unblocked questions with defaults)│
└──────────────────┬────────────────────┘
                   │
                   ▼
┌───────────────────────────────────────┐
│ 2. Issue Formatted Round (Q1..Qn)     │
│    (Questions + Strong Recommendations)│
└──────────────────┬────────────────────┘
                   │
                   ▼
┌───────────────────────────────────────┐
│ 3. Ingest Answers & Advance Frontier  │
│    (Prune resolved, unlock downstream)│
└──────────────────┬────────────────────┘
                   │
                   ▼
┌───────────────────────────────────────┐
│ 4. Verification & Consensus Handshake │
└───────────────────────────────────────┘
PhaseResponsibilityExpected Output
Frontier ExtractionIdentify independent decision nodesFiltered list of unblocked questions
Round FormattingApply standardized Markdown question templatesUser-facing numbered interview round
Downstream UnblockingRe-evaluate tree based on user decisionsUpdated frontier state
Consensus HandshakeSynthesize agreed architecture & requirementsClean brief ready for specification

Step-by-Step Procedure (TWI)

Step 1: Map the Design Space & Compute Frontier

  • Action: Analyze the user's intent, identify all decision nodes, and select only those whose prerequisites are fully settled.
  • Key Point: Filter out any question that requires guessing the answer to an unresolved peer question.
  • Why: Asking dependent questions simultaneously forces the user into speculative, conditional answers that clutter context.

Step 2: Format and Dispatch the Question Round

  • Action: Present the current frontier using the standardized Markdown question format:
    ❓ **Q1** - **<Question Title>**: <Detailed question body and options>
    
    ➡️ **Recommendation**: <Specific proposed answer and technical rationale>
    
    ---
    
    ❓ **Q2** - **<Question Title>**: <Detailed question body and options>
    
    ➡️ **Recommendation**: <Specific proposed answer and technical rationale>
  • Key Point: Keep recommendations opinionated, clear, and grounded in industry best practices.
  • Inline Checklist:
    • Every question numbered and titled
    • Concrete recommendation provided for each question
    • No dependent questions included in the same round

Step 3: Ingest Answers & Advance the Frontier Tree

  • Action: Parse user responses, record settled decisions, unlock newly available downstream questions, and generate the next round.
  • Key Point: If a user response reveals a new unknown in the codebase, dispatch background exploration immediately to resolve it.
  • Why: Real-time background discovery prevents passing factual burdens onto the user.

Step 4: Verify Alignment and Completion

  • Action: Once all branches of the decision tree have been explored and no frontier items remain, present a concise synthesis of all resolved decisions.
  • Key Point: Require explicit user confirmation before proceeding to specification or execution.
  • Why: Mutual alignment guarantees that the subsequent implementation phase proceeds without friction or false assumptions.

Anti-Rationalization Guardrails

Tempting RationalizationBinding RuleEngineering Rationale
"I'll ask just one question now to see what they say."Ask the entire frontier in one turn.Drip-feeding questions creates annoying latency and loses the macro structure of the design.
"Let the user decide without biasing them with my recommendation."Mandatory recommended answer for every question.Concrete recommendations speed up review and give users a clear baseline to react against.
"Ask the user where configuration files or types are defined."Discover environment facts autonomously.User interviews are exclusively for product and architectural decisions, not repo search.
"The user gave a vague answer, but I can guess what they meant."Clarify ambiguous answers immediately.Guessing user intent during grilling undermines the entire purpose of stress-testing.

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