grill-me
Use to grill the user relentlessly about a plan, decision, or idea — a frontier-batched interview down the design tree (rounds of ready questions, each with a…
Skill by KSriki
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/ksriki-grill-me
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: documents, design, testing, writing
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What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.
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Network hosts it talks to 1
codeload.github.com· found in install command
Files it touches
~/.claude/skills/grill-me
What's inside
- Skill name
grill-me- Description
- Use to grill the user relentlessly about a plan, decision, or idea — a frontier-batched interview down the design tree (rounds of ready questions, each with a recommended answer) until confirmed shared understanding, BEFORE any work starts. Triggers on "grill me", "grill this plan", "stress-test my thinking", "poke holes in this", "what am I missing before I build", "interview me about this". Do NOT use to gather facts you could look up yourself (look them up — don't ask), to score model outputs (`eval-harness`), to write the design record (`write-design-doc`), or to decompose a big initiative into tickets (`wayfinder`).
- License
- MIT
- Instructions
- 99 lines in SKILL.md · view on GitHub
Files (1)
- SKILL.md
SKILL.md (first lines)
# Grill me: interrogate the plan before you build
> Adapted from `mattpocock/skills` (MIT), v1.2 — the frontier-rounds rework.
> v1.2 replaced one-question-at-a-time (our previous version) with batched rounds:
> same depth, a third of the turns.
## When to use this
Before committing to a plan or design, when being wrong is cheaper to fix now than
after it's built. The goal is **confirmed shared understanding**, not a vibe check.
**Not this skill if:** you need a discoverable fact — read it, don't ask. You're
scoring outputs → `eval-harness`. You're recording the decision → `write-design-doc`.
You're mapping a large initiative into tickets → `wayfinder`.
## Round 0 — the premise round (before the tree opens)
The design tree has a root every later question silently assumes: **"should this
exist at all?"** Walking the tree without visiting the root is how a model helps
you build a bad idea well. So, before Round 1:
1. **Dispatch `premise-reviewer`** (non-blocking, like any fact subagent) with a
summary of the premise ONLY — never this transcript. Fresh context is the
point: a reviewer that read the enthusiasm is already anchored.
2. **Present its verdict with the first round:** the strongest case against
(provenance-tiered, dated), the proposed kill criteria, and your
recommendation — same ❓/➡️ format as every other question. The user rules on
the premise like any other decision.
3. **Kill criteria are mandatory output.** 2–4 falsifiable *"this was a bad idea
if…"* conditions go into the intent doc. If neither you, the reviewer, nor
the user can name one, say so out loud — that is a finding about the premise,
not a formality to skip.
4. **On RETHINK — warn, then let the human bet.** Flag the tracked issue for a
human decision (`bd human <id>`), present the evidence as *"here's what the
outside view says — are you sure you want to continue?"*, and **pause until
the user explicitly rules**. Silence is not consent — but **an informed
override is a fully legitimate outcome**: contrarian bets are how new things
get built, and this round exists to make the bet *informed*, never to veto
it. An override is recorded in the intent doc (the evidence overridden, the
user's reasoning, kill criteria armed) — that record is what separates a bet
from a blind spot.
5. **Skip condition (stated, never silent):** an internal-only, cheap-to-reverse
change needs no outside view — skip Round 0 and say so in one line.
## The interview: work the question frontier, in rounds
Map the subject as a **design tree** — every decision branches into the decisions
hanging off it. Then:
1. **The frontier** = every decision whose prerequisites are already settled — the
questions you can ask *now* without guessing at answers you haven't heard yet.
2. **Ask the whole frontier in one round.** Number each question and give your
recommended answer, then wait for ALL answers before the next round. A question
that depends on another question still open *this* round belongs to a *later*
round.
3. **Per-question format** (scannable, answer-in-bulk friendly):
```
❓ **Q1 — <question title>**: <question body; may include choices>
➡️ <your recommended answer, and why in a phrase>
```
4. **Each answered round reshapes the tree.** Settled decisions push the frontier
outward; recompute it and ask the next round. Early rounds may be a single
critical question; endgame rounds sweep up the easy ones in one pass.
5. **Facts vs decisions.** Finding *facts* is your job, never the user's — a
frontier question that needs an environment fact gets a **subagent dispatched
non-blocking** (`code-searcher` / `debug-research`): a running exploration is an
unsettled prerequisite, so only its downstream questions wait — ask the rest of
the frontier now. The *decisions* are the user's: put each to them and wait.
6. **Exit:** done when **the frontier is empty** — every branch visited, nothing
left silently assumed. **Do not act until the user confirms** shared
understanding is reached. The confirmation is the gate.
7. **Persist the intent.** On confirmation, write the settled understanding to
`intent/<slug>.intent.md` in the originator's own words: problem, proposed
outcome, affected users/systems, constraints, decisions made, open questions —
plus, from Round 0: the **kill criteria** (falsifiable "this was a bad idea
if…" conditions), the premise verdict, and any **override record** (evidence
overridden + the user's reasoning).
This is the first link of the artifact chain — `write-a-prd` reads it, and a
fresh agent can resume from it without this transcript. Propose the commit;
don't commit unasked (conservative profile).
> Prefer the old cadence? Say "ask one question at a time" — the rounds are a
> default, not a law.
## Definition of done
- [ ] **Round 0 ran** (or its skip was stated in one line): premise verdict presented,
**kill criteria** captured; a RETHINK was ruled on by the human — override or
retreat, but never silence
- [ ] The design tree walked to an **empty frontier** — no branch silently assumed
- [ ] Every question carried a **recommendation**; rounds respected dependencies
- [ ] Facts were **looked up (subagents, non-blocking)**, never asked
- [ ] The human **explicitly confirmed** shared understanding — only then does work start
- [ ] Confirmed understanding persisted as `intent/<slug>.intent.md` — an artifact, not just chatFrom KSriki/agent-harness-template, MIT.
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Signals
- Stars
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- Forks
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- Open issues
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- Last commit (this folder)
- Sep 15, 2026 (1 month ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- MIT
- Repository
- github.com/KSriki/agent-harness-template
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
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Use when building, running, or debugging evaluations for LLM or agent components: golden sets, regression evals, LLM-as-judge, rubric scoring…
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Cite this page
grill-me skill. Agent Mart. https://agentmart.dev/skills/ksriki-grill-me (last updated 2026-10-24)