Grill me

Skill manastalukdar/ai-devstudio/skills/grill-me

Relentlessly interview the user about a plan or design, walking down every branch of the decision tree one question at a time until reaching shared understanding. Use when user wants to stress-test a plan, get challenged on their design, or says "grill me".From its SKILL.md

Install

npx -y skills add manastalukdar/ai-devstudio --skill grill-me

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

One thing to look at

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SKILL.md

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Grill Me

Conduct a relentless interview about every aspect of the current plan or design until reaching shared understanding.

Arguments: $ARGUMENTS - the plan, design, or topic to be grilled on (or leave blank to use current conversation context)

Behavior

Interview relentlessly. Walk down each branch of the decision tree, resolving dependencies between decisions one by one. For each question, provide your recommended answer as a starting point.

Ask exactly one question at a time. Wait for the response before asking the next.

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

Continue until every branch of the decision tree is resolved — not just the obvious ones. Press on:

Why this approach over the alternatives
What happens at the edge cases
How this interacts with existing architecture
What gets harder / what gets easier downstream
What assumptions are baked in that could be wrong
What the rollback looks like if this turns out to be wrong

Do not accept vague answers. If the answer is "it depends", follow up with "depends on what, exactly?"

Examples

/grill-me "add real-time notifications via WebSockets"
/grill-me "migrate from REST to GraphQL"
/grill-me  ← uses current conversation context

Sample Question Sequence

1. What's the primary trigger for a notification — user action, system event, or both?
   → Recommended: system event (decoupled, easier to test)

[wait for answer]

2. Should notifications be persistent (stored + replayable) or fire-and-forget?
   → Recommended: persistent — users expect to see missed notifications on login

[wait for answer]

3. You mentioned Postgres — are you planning to use LISTEN/NOTIFY or a separate message queue?
   → Recommended: LISTEN/NOTIFY for < 10k concurrent users; add Redis if you scale past that

...continues until all branches resolved

Completion Criteria

Stop when:

Every major decision has been made explicitly
Edge cases have been addressed
The user can articulate the approach without ambiguity
No open "it depends" branches remain

Then offer: /write-plan to capture decisions as an implementation plan, or /to-prd to produce a full PRD.

Token Optimization

Expected range: 100–300 tokens per question turn

Codebase exploration: Uses Grep/Bash to verify claims rather than asking questions that can be answered by reading code — avoids unnecessary back-and-forth.

Patterns used: Early exit (stops when all branches resolved), progressive disclosure (one question at a time)

What ships with it

Read from the repository

Just SKILL.md. No reference files, no scripts.