Official agent skill

Asking User Questions

by JetBrains in JetBrains/thinkrail

A skill your agent uses when composing an askuserquestion round inside a workflow, or when a workflow skill names it at a question step.

OfficialApache-2.0Auto-check passedDevelopment

Install Asking User Questions

skills CLI
$ npx skills add JetBrains/thinkrail --skill asking-user-questions -a claude-code

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

GitHub CLI
$ gh skill install JetBrains/thinkrail asking-user-questions --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/JetBrains/thinkrail.git skills-src && mkdir -p .claude/skills && cp -r skills-src/packages/pi-thinkrail-workflow/skills/asking-user-questions .claude/skills/asking-user-questions && 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
asking-user-questions
GitHub stars
514
Token cost
~1.9k tokens
SKILL.md length
1,098 words
Files
1
Skills in repo
11
Repo updated
First seen
Licence
Apache-2.0

At a glance

A skill your agent uses when composing an askuserquestion round inside a workflow, or when a workflow skill names it at a question step.

  • Composing an askuserquestion round inside a workflow
  • SKILL.md covers Interview in rounds until…, Facts are yours, decisions are…, What makes a question worth… and Options, plus 3 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
  • A workflow skill names it at a question step

What it does

Asking User Questions is an agent skill from JetBrains/thinkrail, published by the product's own GitHub organization. Use when composing an askuserquestion round inside a workflow, or when a workflow skill names it at a question step. Shared norms for the tool — not a workflow, nothing to execute.

Its SKILL.md is about 1.9k 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 Development. The repository describes itself as: Vibe code with pi in a lightweight, real IDE that customises itself around the way you work — The Vibe You Need. The licence is Apache-2.0.

When your agent uses it

  • Composing an askuserquestion round inside a workflow
  • A workflow skill names it at a question step

Example prompts

  • “/asking-user-questions”

What it can do on your machine

Read from SKILL.md and the folder at commit 57a1361. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    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

    No URLs in SKILL.md.

    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

Asking User Questions loads about 1.9k tokens when it runs. Until then it costs about 51 tokens; SKILL.md has 1,098 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~51
When it runs · the whole SKILL.md, loaded when a task matches
~1.9k

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 JetBrains/thinkrail at commit 57a1361, republished under its Apache-2.0 licence (© JetBrains). 1,098 words, ~1,872 tokens.

Download SKILL.mdSave it as .claude/skills/asking-user-questions/SKILL.md (or your agent's skills folder).
name
asking-user-questions
description
Use when composing an ask_user_question round inside a workflow, or when a workflow skill names it at a question step. Shared norms for the tool — not a workflow, nothing to execute.

Asking User Questions

The workflow family's shared norms for ask_user_question: how to interview in rounds, what makes a question worth asking, how to shape options, and how to degrade when answers don't come. Process skills name this concept at the steps that ask; when to ask — and where the answers get recorded — stays with the referencing skill.

Interview in rounds until nothing is assumed

  • Map the subject as a design tree: every decision branches into the decisions that hang off it. The frontier is every open decision whose prerequisites are already settled — the questions you can ask now without guessing at answers you haven't heard.
  • One call = one round = the whole frontier, with no cap on its size. A question whose answer depends on another question still open belongs to a later round, never the same one. Never split independent questions across back-to-back calls.
  • The call blocks the current run. Answers arrive as this tool's result. Don't keep working on the blocked step or assume an answer until it arrives — seconds or days later. A composer message sent while the card is open supersedes the round: the card closes unanswered and the message arrives as the next user message, so treat it as the user's reply and re-ask only what still matters.
  • After each round, recompute the frontier: answers settle branches, unblock their dependents, and prune branches that no longer apply. Ask the next round; never pre-write later rounds.
  • The interview is done when the frontier is empty — every branch visited, nothing material silently assumed. Then continue the referencing skill's next step; there is no extra "are we aligned?" round (the referencing skill's own gates still apply).
  • Depth follows the work, not a quota: work with no open user decision gets zero rounds; a decision-heavy change may take several.

Facts are yours, decisions are theirs

  • Never ask the user for a fact the workspace, the specs, or the web can answer. Look it up. When a lookup is slow, start it in the background (a sub-agent, when the host offers one) and ask the rest of the frontier meanwhile — only the questions downstream of that lookup wait.
  • Every decision — scope, observable behavior, trade-offs the user will live with — goes to the user. Picking an option yourself and moving on is answering your own question, not inferring.
  • If candidate options differ only internally — identical observable behavior — it is not a user decision: decide yourself and record the reasoning in the workflow's artifact.

What makes a question worth asking

  • It changes the outcome. Each answer leads somewhere different that the user will see or live with. If every option ends in the same place, drop the question.
  • It is specific to this work. Name the actual feature, screen, file, or user ("when a project is renamed while collapsed…"), never a generic template question.
  • It probes what people silently assume. Sweep the tree's usual blind spots: scope edges and non-goals, empty / error / failure states, edge cases and limits, concurrency or multiple instances, existing data and behavior that must migrate or stay, defaults, and who the work is for.
  • It surfaces tension. A conflict with a recorded spec decision, an earlier answer, or the request itself is asked about outright, quoting both sides.
  • It never re-asks. Anything the request, a prior answer, or the specs already settled is settled; build on it.
  • A concrete scenario beats an abstract principle. Ask "a user drags a file onto a busy session — queue it or reject it?", not "how should concurrency be handled?".
  • If the question can't be settled by talking (how something should look or feel), show a concrete artifact in options[].preview — a mockup, snippet, or config — instead of describing it.
Show full SKILL.md (483 more words)Show less

Options

  • Recommended option first, label suffixed "(Recommended)", plus a one-line recommendedReason saying why you recommend it over the alternatives (shown inline under the option as a Why: line).
  • Every option: a concise label (1–5 words, ≤ 60 chars) + a description carrying the trade-off or consequence of choosing it. Tailor options to the work at hand — never generic placeholders.
  • Options must be decidable by the asked user: frame them as observable behavior or outcomes ("collapsing a project stays collapsed after a rename"), never as implementation mechanics ("semantic guard", "activation ref").
  • Never author your own "Other", free-text, or escape options — the tool adds a free-text row to every question and an always-available Skip, and reserved labels are rejected. This holds under multiSelect too: the free-text row stays and is additive — a typed answer arrives alongside the checked options, it does not replace them.
  • multiSelect: true when several answers are valid at once (feature checklists); single-select when confirming something or choosing one path.
  • options[].preview (markdown) when a concrete artifact — code, a config, a mockup — is clearer shown than described. Single-select only.
  • header is a short chip, ≤ 16 characters.

Confirming an inference

When you have inferred something and need a yes/adjust rather than an open answer: the inferred statement is the question text, with "Looks right" as the first option (description: "accurate as written") and a genuine rejection option second (e.g. "Off base — ask me directly"). Edits arrive through the tool's automatic free-text row — do not author an edit option. Read the response as:

  • "Looks right" → the inference holds; continue unchanged.
  • Free-text tweak (one fact changes) → update that field only; don't re-derive anything else.
  • Substantial rewrite → re-derive every inference that came from that statement before continuing.
  • Rejection → discard the inference entirely and ask an open-ended question instead.

Degradation

  • A skipped or declined question is not a blocker: settle it on your recommended answer, recorded as unconfirmed in the workflow's artifact (the referencing skill says where), and keep working its dependents from that assumption — don't re-ask it.
  • A whole round skipped means the user wants to stop being interviewed: ask no further rounds and proceed on recorded assumptions for everything still open.
  • If the host reports no interactive UI (ask_user_question returns "not available"), state your assumptions the same way instead of blocking.
  • "I don't know / help me understand" is a mis-framing signal, not a missing-knowledge one: re-explain from user-visible behavior in plain language, then re-ask with behavior-framed options — don't repeat the same technical options with more detail.

Red flags

  • You stopped after one round while decisions that depended on its answers are still open.
  • You chose an option for the user instead of asking — or asked the user something you could have looked up.
  • One round holds two questions where one answer would change the other.
  • A question restates what the request or an earlier answer already settled.
  • Every question would fit any project — nothing names this work's specifics.

© JetBrains, Apache-2.0. 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 packages/pi-thinkrail-workflow/skills/asking-user-questions of JetBrains/thinkrail.

Open the folder on GitHubat commit 57a1361

Compare with similar skills

Asking User Questions 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.

Asking User Questions compared with similar skills
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Asking User Questions this skillJetBrains/thinkrail514—~1.9kAutomated safety check: PassApache-2.0
Vercel Composition Patternssupabase/supabase111k58 repos~726Automated safety check: PassMIT
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PR Babysitteropeninterpreter/openinterpreter69k3 repos~4.2kAutomated safety check: PassApache-2.0
Code Review ChecklistshareAI-lab/learn-claude-code78k4 repos~1.1kAutomated safety check: PassMIT

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Categories

Questions about Asking User Questions

What does Asking User Questions do?

A skill your agent uses when composing an askuserquestion round inside a workflow, or when a workflow skill names it at a question step. Asking User Questions is an agent skill from JetBrains/thinkrail, published by the product's own GitHub organization. Use when composing an askuserquestion round inside a workflow, or when a workflow skill names it at a question step.

When should I use Asking User Questions?

Asking User Questions fits situations like: composing an askuserquestion round inside a workflow; A workflow skill names it at a question step.

How do I install Asking User Questions in Claude Code?

Run `npx skills add JetBrains/thinkrail --skill asking-user-questions -a claude-code`. Or copy the skill folder (packages/pi-thinkrail-workflow/skills/asking-user-questions in JetBrains/thinkrail) into .claude/skills/asking-user-questions in your project. Claude Code loads it when a task matches its description.

How do I install Asking User Questions in Codex?

Run `npx skills add JetBrains/thinkrail --skill asking-user-questions -a codex`. Or copy the skill folder (packages/pi-thinkrail-workflow/skills/asking-user-questions in JetBrains/thinkrail) into .agents/skills/asking-user-questions in your project. Codex loads it when a task matches its description.

Can I use Asking User Questions 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 JetBrains/thinkrail --skill asking-user-questions -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/asking-user-questions, .gemini/skills/asking-user-questions, .github/skills/asking-user-questions and .opencode/skills/asking-user-questions in your project.

What does Asking User Questions need to run?

SKILL.md names no scripts, command-line tools or credentials: Asking User Questions is instructions for the agent only.

Does Asking User Questions access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Asking User Questions 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 Asking User Questions use?

Asking User Questions is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Asking User Questions use?

About 1.9k tokens (SKILL.md is roughly 7.5k 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 Asking User Questions?

Skills that share tags, products or a category with Asking User Questions: Vercel Composition Patterns (supabase/supabase, 111k stars), Finishing a Development Branch (obra/superpowers, 297k stars), Typescript Advanced Types (rolling-scopes/rsschool-app, 10k stars) and PR Babysitter (openinterpreter/openinterpreter, 69k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Asking User Questions?

JetBrains (a GitHub organization, an official publisher) maintains it in JetBrains/thinkrail, which has 514 GitHub stars. The repository holds 11 skills in this directory. The repository was last updated on October 10, 2026.

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