Agent skill

Grill Me

by nrwl in nrwl/nx

Grill the user relentlessly about a plan, design, decision, or set of review findings — working the decision tree in rounds until nothing is left silently assumed.

MITAuto-check passedAgent Workflows

Install Grill Me

skills CLI
$ npx skills add nrwl/nx --skill grill-me -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install nrwl/nx grill-me --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/nrwl/nx.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.claude/skills/grill-me .claude/skills/grill-me && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
grill-me
GitHub stars
29k
Token cost
~1.2k tokens
SKILL.md length
687 words
Files
1
Skills in repo
21
Repo updated
First seen
Licence
MIT

At a glance

Grill the user relentlessly about a plan, design, decision, or set of review findings — working the decision tree in rounds until nothing is left silently assumed.

  • Works in 3 steps: Round 1 — the blocking findings. They… → Round 2 — the rest, plus what round 1… → Round 3 — the consequences. The verdict…
  • The user wants to stress-test their thinking
  • SKILL.md covers Two rules that hold regardless… and When a caller delegates a set…
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Grill Me is an agent skill from nrwl/nx. Grill the user relentlessly about a plan, design, decision, or set of review findings — working the decision tree in rounds until nothing is left silently assumed. Use when the user wants to stress-test their thinking, says "grill me", or when another skill (for example /review-pr) delegates its evaluation pass here.

Its SKILL.md is about 1.2k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Agent Workflows, covering Requirements gathering, Code review and Pull requests. The repository describes itself as: The Monorepo Platform that amplifies both developers and AI agents. Nx optimizes your builds, scales your CI, and fixes failed PRs automatically. Ship in half the time. The licence is MIT.

When your agent uses it

  • The user wants to stress-test their thinking
  • Another skill (for example /review-pr) delegates its evaluation pass here

Example prompts

  • “grill me”
  • “/grill-me”

Requirements

  • Pre-approved tools (allowed-tools): Read, Grep, Glob, Bash(git -C *), Bash(git log *), Bash(git diff *), Bash(git show *), Bash(gh pr view *), Bash(gh issue view *), Agent, AskUserQuestion, Edit(*), Write(*)

Workflow steps

3 steps, taken from the first numbered list in SKILL.md.

  1. Round 1 — the blocking findings. They gate the verdict, and they are independent of one another, so the whole tier is one frontier.
  2. Round 2 — the rest, plus what round 1 unblocked. Dropping one finding as pre-existing usually implicates its siblings in the same file or…
  3. Round 3 — the consequences. The verdict that follows from what survived, and anything the user's reasoning generalized into a standing rule.

What it can do on your machine

Read from SKILL.md and the folder at commit 200edc8. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves these tools, so the agent can use them without asking each time:

    • Read
    • Grep
    • Glob
    • Bash(git -C *)
    • Bash(git log *)
    • Bash(git diff *)
    • Bash(git show *)
    • Bash(gh pr view *)
    • Bash(gh issue view *)
    • Agent

    …and 3 more on the same allowed-tools line.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Links to these hosts (documentation or services it may open):

    • github.com

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Grill Me loads about 1.2k tokens when it runs. Until then it costs about 82 tokens; SKILL.md has 687 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~82
When it runs · the whole SKILL.md, loaded when a task matches
~1.2k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from nrwl/nx at commit 200edc8, republished under its MIT licence (© nrwl). 687 words, ~1,235 tokens.

Download SKILL.mdSave it as .claude/skills/grill-me/SKILL.md (or your agent's skills folder).
name
grill-me
description
Grill the user relentlessly about a plan, design, decision, or set of review findings — working the decision tree in rounds until nothing is left silently assumed. Use when the user wants to stress-test their thinking, says "grill me", or when another skill (for example /review-pr) delegates its evaluation pass here.
allowed-tools
Read, Grep, Glob, Bash(git -C *), Bash(git log *), Bash(git diff *), Bash(git show *), Bash(gh pr view *), Bash(gh issue view *), Agent, AskUserQuestion, Edit(*), Write(*)

Interview the user relentlessly until you reach a shared understanding. Map the subject as a design tree: every decision branches into the decisions that hang off it.

Work the tree in rounds. The frontier is every decision whose prerequisites are already settled — the questions you can ask now without guessing at answers you haven't heard yet. Ask the whole frontier in one round: number each question and give your recommended answer. Then wait for the user's answers before the next round.

Format each question like so:

❓ **Q1** - **<question title>**: <question body, may be several paragraphs, including any choices>

➡️ <your recommended answer>

Each round of answers reshapes the tree — settled decisions push the frontier outward and unblock questions that depended on them. Recompute the frontier and ask the next round. A question whose answer depends on another question still open in this round belongs to a later round, not this one.

Finding facts is your job, never the user's. When a frontier question needs a fact from the environment, dispatch a sub-agent to find it — never ask the user for something you could look up. Don't block on it: a running exploration is an unsettled prerequisite, so only the questions downstream of it wait: ask the rest of the frontier now. The decisions are the user's — put each to them and wait.

The session is done when the frontier is empty: every branch visited, nothing left silently assumed. Do not act on the outcome until the user confirms you have reached shared understanding.

Two rules that hold regardless of caller

  • Never answer your own questions. If a round goes unanswered, stop and leave the subject exactly as it was. A grill that supplies the user's answers manufactures agreement that was never given, and every downstream step that trusts the result inherits the fabrication. Silence means stop, not proceed with the obvious answer.
  • Skip what is already settled. A question the caller's own material answers is noise. The point is resolving genuine uncertainty, not walking a checklist.
Show full SKILL.md (367 more words)Show less

When a caller delegates a set of findings

Brief the user before the first question. Unlike a plan they wrote themselves, findings arrive from agents the user has not read — so state, up front, what was reviewed and the one-line inventory of findings by tier. Then have every question restate the finding it is about, inline, rather than referring to it by number. A question about a defect the user has never seen is unanswerable, and rule one below turns an unanswered question into a full stop — so opening cold does not make the grill cautious, it makes it produce nothing.

Review findings are mostly independent of each other, so the tree is shallow and wide rather than deep. Round it anyway — the dependencies are real, they just sit between tiers rather than between individual items:

  1. Round 1 — the blocking findings. They gate the verdict, and they are independent of one another, so the whole tier is one frontier.
  2. Round 2 — the rest, plus what round 1 unblocked. Dropping one finding as pre-existing usually implicates its siblings in the same file or pattern; those questions could not be asked until round 1 landed.
  3. Round 3 — the consequences. The verdict that follows from what survived, and anything the user's reasoning generalized into a standing rule.

Apply each round's answers before asking the next, rather than collecting everything and acting at the end — the user should be able to stop after any round and keep the value of what is already decided.

Close by briefing again. When the frontier is empty, re-render the opening inventory against the post-grill state, showing what moved — dropped, re-tiered, kept — and ask whether it matches what the user decided. Answers are given one round at a time against one item at a time, so nobody tracks the cumulative effect in their head, and the material has been mutating the whole way. This is a confirmation, not another round: do not reopen a settled item or raise something the grill never asked about. If the user's reply opens something genuinely new, that is a new round — grill it properly.


The round/frontier method above is adapted from mattpocock/skills (skills/productivity/grilling), MIT-licensed, © 2026 Matt Pocock.

© nrwl, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in .claude/skills/grill-me of nrwl/nx.

Open the folder on GitHubat commit 200edc8

Compare with similar skills

Grill Me next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Grill Me compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Grill Me this skillnrwl/nx29k—~1.2kAutomated safety check: PassMIT
Deep Divebyungjunjang/jangpm-meta-skills120—~2.5kAutomated safety check: PassNone
Grill With Docsmeain/dotfiles28520 repos~875Automated safety check: PassMIT
Grill With Docsayoubben18/ab-method192—~2.1kAutomated safety check: PassMIT
Grill Memacalbert/envilder138—~1kAutomated safety check: PassMIT
Grill With Docsalirezarezvani/claude-skills28k—~1.8kAutomated safety check: PassMIT

Similar skills

  • Deep Dive

    byungjunjang/jangpm-meta-skills

    Socratic interview skill to deepen a spec or refine an existing agent blueprint.

    120 GitHub stars~2.5k tokensUpdated 2 mo ago
    Agent WorkflowsAuto-check passed
  • Grill With Docs

    meain/dotfiles

    Grilling session that challenges your plan against the existing domain model, sharpens terminology, and updates documentation (CONTEXT.md, ADRs) inline as decisions crystallise.

    285 GitHub starsUsed in 20 repos~875 tokens
    DevelopmentAuto-check passed
  • Grill With Docs

    ayoubben18/ab-method

    Grilling session that challenges your plan against the existing domain model, sharpens terminology, and updates documentation (CONTEXT.md, ADRs) inline as decisions crystallise.

    192 GitHub stars~2.1k tokensUpdated 9 days ago
    DevelopmentAuto-check passed
  • Grill Me

    macalbert/envilder

    Grilling session that challenges a plan against the existing domain model, sharpens terminology, and updates documentation (CONTEXT.md, ADRs) inline as decisions crystallise.

    138 GitHub stars~1k tokensUpdated 5 days ago
    Agent WorkflowsAuto-check passed
  • Grill With Docs

    alirezarezvani/claude-skills

    Docs-anchored grilling session — challenges a plan against the project's existing language (CONTEXT.md) and recorded decisions (docs/adr/), and updates those files inline as terminology and…

    28k GitHub stars~1.8k tokensUpdated 1 mo ago
    DevelopmentAuto-check passed
  • Model Domain

    danielvm-git/bigpowers

    Grilling session that challenges your plan against the existing domain model, sharpens terminology, and updates specs/tech-architecture/tech-stack.md and specs/adr/ inline as decisions crystallise.

    260 GitHub stars~1.2k tokensUpdated 18 days ago
    DevelopmentAuto-check passed
  • Monitor CI

    nrwl/nx

    Monitor Nx Cloud CI pipeline and handle self-healing fixes. An agent skill from nrwl/nx.

    29k GitHub starsUsed in 6 repos~4.7k tokens
    Auto-check passed
  • Nx Import

    nrwl/nx

    Import, merge, or combine repositories into an Nx workspace using nx import.

    29k GitHub starsUsed in 6 repos~3.5k tokens
    Auto-check passed
  • Run Nx generators with prioritization for workspace-plugin generators.

    29k GitHub starsUsed in 2 repos~592 tokens
    Auto-check: notes
  • Author or scope a first-party Nx migration. An agent skill from nrwl/nx.

    29k GitHub stars~12k tokensUpdated today
    Auto-check: notes
  • Generate code using nx generators. An agent skill from nrwl/nx.

    29k GitHub starsUsed in 1 repo~2.2k tokens
    Auto-check passed
  • Check modified Nx documentation pages against the astro-docs style guide.

    29k GitHub stars~1.3k tokensUpdated today
    Auto-check passed

Questions about Grill Me

What does Grill Me do?

Grill the user relentlessly about a plan, design, decision, or set of review findings — working the decision tree in rounds until nothing is left silently assumed. Grill Me is an agent skill from nrwl/nx. Grill the user relentlessly about a plan, design, decision, or set of review findings — working the decision tree in rounds until nothing is left silently assumed.

When should I use Grill Me?

Grill Me fits situations like: the user wants to stress-test their thinking; another skill (for example /review-pr) delegates its evaluation pass here.

How do I install Grill Me in Claude Code?

Run `npx skills add nrwl/nx --skill grill-me -a claude-code`. Or copy the skill folder (.claude/skills/grill-me in nrwl/nx) into .claude/skills/grill-me in your project. Claude Code loads it when a task matches its description.

How do I install Grill Me in Codex?

Run `npx skills add nrwl/nx --skill grill-me -a codex`. Or copy the skill folder (.claude/skills/grill-me in nrwl/nx) into .agents/skills/grill-me in your project. Codex loads it when a task matches its description.

Can I use Grill Me in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add nrwl/nx --skill grill-me -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/grill-me, .gemini/skills/grill-me, .github/skills/grill-me and .opencode/skills/grill-me in your project.

What does Grill Me need to run?

SKILL.md names no scripts, command-line tools or credentials: Grill Me is instructions for the agent only. Its frontmatter pre-approves these tools: Read, Grep, Glob, Bash(git -C *), Bash(git log *), Bash(git diff *), Bash(git show *), Bash(gh pr view *), Bash(gh issue view *), Agent, AskUserQuestion, Edit(*), Write(*).

Does Grill Me access the network?

SKILL.md names 1 domain. As links in the text: github.com. This is read from the text; nothing was executed.

Is Grill Me safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Grill Me use?

Grill Me is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Grill Me use?

About 1.2k tokens (SKILL.md is roughly 4.9k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Grill Me?

Skills that share tags, products or a category with Grill Me: Deep Dive (byungjunjang/jangpm-meta-skills, 120 stars), Grill With Docs (meain/dotfiles, 285 stars), Grill With Docs (ayoubben18/ab-method, 192 stars) and Grill Me (macalbert/envilder, 138 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Grill Me?

nrwl (a GitHub organization) maintains it in nrwl/nx, which has 29,401 GitHub stars. The repository holds 21 skills in this directory. The repository was last updated on October 10, 2026.

Source: nrwl/nx on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.