←Leaderboard/Software Engineering/thinkrail
Last commit on October 14, 2026·Created on July 8, 2026

JetBrains/thinkrail

“A framework for structuring agentic workflows through spec-driven development and user interaction.”
Combined rank
#485
across all skills
In Software Engineering
#42
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TL;DR

Thinkrail provides a set of structured norms for AI agents to navigate the development lifecycle. It emphasizes rigorous preparation, requiring brainstorming phases before any feature implementation or bug fix to ensure behavioral changes are intentional.

The system helps automation builders compose reliable workflows by defining how agents should choose a path and handle user question rounds, moving from vague requests to structured execution.

WHO IT'S FOR
AI agent / automation builders
designing spec-driven AI coding workflows
Technical leads / architects
establishing spec-driven development norms
Software engineers using AI assistants
onboarding existing projects to agentic tools
Platform / DevEx teams
standardizing AI-driven PR lifecycle work
Compatible AgentsThe repository documents support for these agents. The skills may also work with other agents that can load SKILL.md files, but they may need some setup or small changes.

Use this skill collection

Follow the documented setup, then try a first task.

ThinkRail CLI for macOS or Linux

Installs: ThinkRail application with its bundled workflows; not a standalone skill installation. · ThinkRail

Before you start
  • git on PATH.
  • A model provider: sign in with JetBrains AI in the app or supply your own provider credentials.
  • Bash and curl.
  • sha256sum or shasum for checksum verification.
  • On Apple Silicon, use a native arm64 shell.

Platform: macOS Apple Silicon; Linux x64 or ARM64. Intel macOS has no prebuilt CLI.

  1. Run this command in a terminal to download the binary, verify its checksum, and install it on PATH.

    curl -fsSL https://raw.githubusercontent.com/JetBrains/thinkrail/main/install.sh | bash
  2. Launch ThinkRail, then sign in with JetBrains AI or configure your own model provider credentials.

install.sh ↗ · Checked Oct 18, 2026README.md ↗ · Checked Oct 18, 2026

Give it something to do.

Suggested first task

Understand one module through its specs

Uses spec-graph

  • An accessible project with an existing spec graph.
  • The module name or path to investigate.
  • Available spec_grep, spec_get, and spec_graph tools.

Make sure spec-graph is installed in your agent before trying this task.

Use the spec-graph skill to find the specs governing the module I identify. Read only the relevant graph neighborhood and summarize the module's purpose, boundaries, and recorded decisions. Surface any contradictions you notice without changing files.
Suggested first task

Turn a small project idea into a goal document

Uses starting-a-new-project

  • An empty workspace with no source code or existing spec graph.
  • A short description of your personal project idea.
  • The writing-specs and asking-user-questions companion skills and spec tools.

Make sure starting-a-new-project is installed in your agent before trying this task.

Use the starting-a-new-project skill for my small personal project idea in this empty workspace. Help me confirm the problem and smallest useful capabilities, then save a concise goal-and-requirements.md incrementally and present it for review.
Suggested first task

Clarify a small feature before implementation

Uses brainstorming

  • An accessible project and a description of one small feature.
  • The project's relevant specs.
  • The spec-graph and asking-user-questions skills and spec tools.

Make sure brainstorming is installed in your agent before trying this task.

Use the brainstorming skill to design the small feature I describe. Consult the relevant specs, clarify the user-visible behavior and acceptance criteria, and record a concise draft task-spec with the proposed approach and trade-offs. Stop after presenting the design for my review.