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asking-user-questions

@jetbrains⭐ 887 stars

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.

Choose how to use this skill

You do not need every option. Choose the path your AI client supports. The stable page stays the same; versioned files are immutable.

1. Native installer

This listing has no registered native installer command. Use the complete package or source fallback below, depending on what your client supports.

Do not guess an installer command or replace an existing version without reviewing the diff.

2. Complete package recommended

Download the ZIP when available. It includes SKILL.md plus the references, security notes and version metadata.

No complete ProSkills package is published for this listing yet.

3. Prompt-only

Copy the prompt above when the agent can read the stable page or when you want to adopt the workflow without installing a skill.

Need only the instruction file?

Download SKILL.md only if your client requires a single file. The complete ZIP is safer for a full installation because it preserves the references and release context.

No path installs or executes anything by itself. Your agent still needs access to the project files. Before updating, compare the installed version and review the diff.

—/10

// RATINGS

⭐GitHub Stars
⭐⭐⭐⭐ 887 on GitHubGitHub ↗

Popular

🟢ProSkills Score
—
📍

Not yet listed on ClawHub or SkillsMP

// README

ThinkRail

JetBrains incubator project

ThinkRail is the agentic IDE that gets better every time you use it — learning your project through living specs today, and building its own capabilities tomorrow.

We built a rich interface around the pi coding agent, isolated work into separate workspaces, and gave the agent durable project knowledge through living specs and reusable skills. Next, we're adding full extension support, so ThinkRail can create the tools it needs based on how you actually work.

Website: thinkrail.ai · Blog: thinkrail.ai/blog

A pi session and the change it made, scoped to an isolated git-worktree workspace.

What you get

  • Isolated workspaces. Open any git repo as a project and cut workspaces from it as git worktrees, each with its own branch and working directory. Agents work in parallel without touching your checkout; merge the good branch, delete the rest. You can also attach existing worktrees or explicitly work in the project folder itself. Finished and dormant workspaces settle onto a per-project shelf on their own — when their pull request merges or closes, or after a quiet week — and come back the moment you work in them.
  • A real IDE around the agent. A splittable workbench of Monaco editor tabs, a live git Changes view, terminals, and documents — all scoped to the active workspace. Leave anchored review comments on files and diffs and send them to a chat as structured context, or open the worktree in your installed IDE.
  • Chats that stream like the engine thinks. Several concurrent pi sessions per workspace, each with its own model and live token and cost readout. Steer a running turn or queue a follow-up, delegate to subagents, and work a shared plan the agent updates and you edit — each completed step can be committed and reviewed on its own.
  • Specs as ground truth. A connected graph of SPEC.md files lives beside the code; the agent reads, searches, and maintains it through dedicated spec_* tools, so intent survives the session. The read-only Specs tool renders the graph as a tree in the workbench.
  • Skills and workflows. Portable Agent Skills you already keep for other coding agents are read in place, and bundled workflows guide project setup, design brainstorming, and shipping a pull request — pushing the workspace branch and opening or updating its GitHub PR through your own gh.
  • Agent tools beyond the shell. Web research, and inline diagrams and option comparisons rendered right in the chat. Settings → Extensions lists the ThinkRail extensions the agent gets and lets you switch each one off.
  • MCP servers. Connect the MCP servers in your pi mcp.json (or add them, and a few presets, from Settings): ThinkRail asks in the chat before calls the server does not mark read-only (or always allows the tools you trust in a project), keeps servers a repository defines off until you approve them, signs you in to OAuth servers from Settings, and shows each chat's servers next to its background commands and subagents.
  • Your providers, your credentials. Sign in with JetBrains AI or connect any provider through pi's own auth. ThinkRail has no accounts of its own.
  • Desktop app or browser. A native desktop app, or the thinkrail CLI that opens the same app in your browser. Both embed the same engine host; app state lives under ~/.thinkrail.

The project's spec graph as a tree, with the spec itself rendered alongside.

Install

ThinkRail ships in two additive forms: a native desktop installer and the self-contained thinkrail CLI. Both are published with SHA256SUMS on the releases page.

Desktop

Download the thinkrail-desktop-* asset for your platform:

  • macOS (Apple Silicon) — open the DMG. There is no Intel desktop build.

  • Windows x64 — extract the complete setup ZIP, then run its setup executable in place, next to its payload.

  • Linux x64 / ARM64 — extract the setup tarball and run installer. Desktop builds need glibc 2.38+ with GTK 3, WebKitGTK 4.1, Ayatana AppIndicator 3, and librsvg 2 — Ubuntu 24.04 or newer:

    sudo apt install libgtk-3-0 libwebkit2gtk-4.1-0 libayatana-appindicator3-1 librsvg2-2
    

Packaged stable and nightly desktop builds check for updates in the background and offer them in Settings → Updates: Download → Preparing update → Install & Restart. Nothing is applied until you choose Install & Restart. The updater appears only when the package carries a valid HTTPS feed identity; installations that predate that identity need one manual installation first.

Command line

The installer downloads the right binary, verifies its SHA-256 checksum, and puts thinkrail on your PATH.

macOS / Linux (also Windows under Git Bash):

curl -fsSL https://raw.githubusercontent.com/JetBrains/thinkrail/main/install.sh | bash

Windows — the same command works from cmd and PowerShell:

powershell -c "irm https://raw.githubusercontent.com/JetBrains/thinkrail/main/install.ps1 | iex"

Then run thinkrail, optionally with a git repo to open as a project:

thinkrail ~/code/my-repo

thinkrail needs git on your PATH and a model provider — sign in with JetBrains AI from the app or use your own provider credentials. thinkrail --help lists the flags; thinkrail --version prints the build.

The installer takes --channel stable|nightly and --version; a pinned version must belong to the selected channel:

curl -fsSL https://raw.githubusercontent.com/JetBrains/thinkrail/main/install.sh | bash -s -- --channel nightly
curl -fsSL https://raw.githubusercontent.com/JetBrains/thinkrail/main/install.sh | bash -s -- --channel stable --version 0.1.2
curl -fsSL https://raw.githubusercontent.com/JetBrains/thinkrail/main/install.sh | bash -s -- --channel nightly --version 0.2.0-nightly.10

On Windows the options are environment variables (THINKRAIL_CHANNEL, THINKRAIL_VERSION, THINKRAIL_PREFIX, THINKRAIL_NO_MODIFY_PATH):

$env:THINKRAIL_CHANNEL='nightly'; irm https://raw.githubusercontent.com/JetBrains/thinkrail/main/install.ps1 | iex   # PowerShell
set "THINKRAIL_CHANNEL=stable" && set "THINKRAIL_VERSION=0.1.2" && powershell -c "irm https://raw.githubusercontent.com/JetBrains/thinkrail/main/install.ps1 | iex"   # cmd

Installed stable and nightly CLI hosts periodically offer Run Update in Settings → Updates. It runs the host machine's thinkrail update in the background — also when the UI is open in a browser on another machine — and a successful update asks you to restart the host manually. You can run thinkrail update directly on any platf

// HOW IT'S BUILT

KEY FILES

packages/pi-thinkrail-workflow/skills/asking-user-questions/SKILL.mdREADME.md

// REPO STATS

887 stars