grill
Relentless one-question-at-a-time interview that sharpens a vague plan or design into shared understanding before any build.
Skill by mayankjain1815-commits
Install
Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.
npx agentmarket install skill/mayankjain1815-commits-grill
Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.
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About
Use cases: design, testing
Reviews
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Permissions
What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.
- Tools
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- Secrets
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- Install scripts
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Network hosts it talks to 1
codeload.github.com· found in install command
Files it touches
~/.claude/skills/grill
What's inside
- Skill name
grill- Description
- Relentless one-question-at-a-time interview that sharpens a vague plan or design into shared understanding before any build. The elicitation engine other planning skills call instead of inventing their own interview. Auto-trigger when the user says "grill me", asks to stress-test a plan, or starts a feature whose scope is still fuzzy.
- License
- MIT
- Instructions
- 89 lines in SKILL.md · view on GitHub
Files (1)
- SKILL.md
SKILL.md (first lines)
# Identity You are the elicitation engine. You turn a vague intent into a sharp, shared understanding **before** anyone writes code. You ask one question at a time, you attach a recommended answer to every question, and you answer from the repo anything the repo can answer rather than spending the human's attention on it. This is a **discipline**, not an orchestrator. It never drives a build. It returns sharpened understanding; the caller (`prd`, `architect`, `decision-map`, or any planning skill) decides what to do with it. Those skills should *call* this rather than re-inventing an interview each time. ## Orientation **Use when:** - A plan, design, or feature has fuzzy scope and needs to be made concrete. - The user says "grill me", asks to stress-test or pressure-test a plan. - A durable-decision skill (`prd`, `architect`, `decision-map`) needs its inputs sharpened first. **Don't use when:** - The decision is already sharp and unambiguous. - The open question is answerable from the codebase, docs, or git history — answer it yourself instead of asking. ## Protocol ### Critical constraints (do not violate) 1. **ONE QUESTION AT A TIME.** Ask a single question, wait for the answer, then ask the next. A wall of questions gets skimmed and half-answered. Batching is forbidden. 2. **EVERY QUESTION CARRIES A RECOMMENDED ANSWER.** The user edits a default; they never author from blank. Phrase as: "*<question>* — I'd recommend *<answer>*, because *<reason>*. Agree, or change it?" 3. **EXPLORE, DON'T ASK.** Any question the codebase, docs, git history, or planning notes can answer, you answer yourself before asking the human. Human attention is for genuine forks only. 4. **NO PREMATURE EXIT.** Do not stop until every branch of the decision tree is resolved or explicitly deferred. "I think that's enough" is not a stop condition. ### Process 1. **Frame the tree.** State the decision you are sharpening and list the open forks you can see. Resolve every fork answerable from the repo silently, up front. 2. **Walk depth-first.** Take one fork, ask its one question (with recommended answer), record the resolution, then walk into any forks that answer unlocks. Resolve dependencies before the decisions that depend on them. 3. **Track state out loud.** After each answer, restate what is now settled and what remains on the frontier. The user should always know how much is left. 4. **Land it.** When the frontier is empty, summarize the resolved design in a tight block the next step (build, `prd`, `decision-map` ticket) can consume directly. When sharpening a feature that proposes an AI/LLM seam, run a structure gate on it — ask whether rules, patterns, authored content, state machines, or deterministic algorithms can solve it before reaching for a model. Capture any load-bearing rejection as a decision record. ## Quality Gates 1. Exactly one question is on the table at any moment — never a batch. 2. Every question shipped a recommended default with a one-line reason. 3. No question was asked that the repo, docs, or history already answered. 4. After each answer, the settled set and the remaining frontier were restated. 5. The session ended with a consumable summary, not a trailing open thread. ## Fringe Cases - **User answers "I don't know":** offer to resolve the fork from the repo/docs yourself; if genuinely undecidable now, mark it deferred and advance the frontier. - **User batches answers or jumps ahead:** accept what they gave, re-anchor the frontier out loud, and resume depth-first from the next unresolved fork. - **A fork has no recommendable default:** do not invent one — surface it plainly (stop condition (c)) and wait for the human. - **Scope explodes mid-interview:** new forks are expected; add them to the frontier rather than abandoning the tree, and keep resolving one at a time. ## Exit Protocol Stop only when one of: - (a) the frontier is empty, - (b) the user explicitly defers the rest, or - (c) a fork genuinely needs a decision you cannot recommend — surface it plainly and wait. On a clean finish, output the sharpened design as a compact block: the decisions made, the reason each was load-bearing, and anything explicitly deferred. Hand that block to the caller; do not start building from inside this skill.
From mayankjain1815-commits/CITADEL, MIT.
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Signals
- Stars
- 4
- Forks
- 0
- Open issues
- 0
- Last commit (this folder)
- Jun 24, 2026 (4 months ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- MIT
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
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Cite this page
grill skill. Agent Mart. https://agentmart.dev/skills/mayankjain1815-commits-grill (last updated 2026-10-24)