linearis-oss/linearis — CLI tool for Linear.app with JSON output, smart ID resolution, and optimized GraphQL queries.

Description and use

**Brief Summary**
Linearis is a TypeScript‑based CLI for Linear.app that returns data as clean JSON, resolves issue IDs intelligently, and uses optimized GraphQL queries. It is built for both LLM agents and developers who need structured, machine‑readable output, making it easy to plug Linear data into AI‑driven workflows.

**Value**

• **AI‑ready interface** – By exposing Linear data in a predictable JSON format, Linearis removes the need to hand‑craft GraphQL queries or scrape HTML, letting teams add AI features (e.g., RAG, autonomous agents) with minimal boilerplate.
• **Productivity boost** – The smart ID resolution lets users refer to issues, projects, or cycles using partial names or aliases, streamlining scripting and prompt engineering.
• **Low‑cost experimentation** – Because the tool is open source and already handles authentication, pagination, and rate‑limit management, teams can prototype AI‑enhanced product‑management bots or analytics dashboards without building a custom integration stack.

**Practical Adoption Path**

1. **Evaluate** – Clone the repo, run npx linearis <command> with a personal Linear API token, and verify the JSON output matches your use case.
2. **Integrate** – Wrap the CLI (or import its underlying TypeScript SDK) in your existing CI/CD or LLM orchestration layer (e.g., LangChain, CrewAI).
3. **Extend** – Add custom post‑processing scripts or prompt templates that consume the JSON, then iterate on your agent or RAG pipeline.
4. **Deploy** – Package the CLI in a Docker image or as a serverless function to provide a stable endpoint for downstream services.

**Production Readiness**

• **Activity & Community** – 223 ★, 21 forks, recent commits (last updated 2026‑07‑02), and a clear TypeScript codebase indicate an active project.
• **Stability** – The CLI abstracts GraphQL intricacies and includes built‑in pagination and error handling, which reduces runtime failures in production.
• **Ecosystem Fit** – Straightforward installation via npm, well‑documented commands, and JSON‑first output make it compatible with most AI orchestration tools.
• **Risks** – License compliance, security scanning of dependencies, and long‑term maintainer commitment still need a final check, but no major metadata concerns were found.

Overall, Linearis is mature enough for a pilot or even a production‑grade integration, especially when the goal is to add AI‑driven capabilities to Linear workflows without building a custom GraphQL client from scratch.

Problem

linearis-oss/linearis helps add AI capability without starting from a blank model stack.

Outcome

High for an OSS candidate: recent activity, adoption, and ecosystem signals are strong enough for a serious pilot.

Workflow

• prototype AI features
• build RAG or agent workflows
• evaluate model tooling

Evidence

CLI tool for Linear.app with JSON output, smart ID resolution, and optimized GraphQL queries. Designed for LLM agents and humans who prefer structured data.

Source