linearis: CLI tool for Linear.app with JSON output, smart ID resolution, and optimized GraphQL queries

by czottmann · Agent Tool · ★ 170

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

How to install linearis

npm install -g linearis

Taken from the project's README on GitHub.

Security audit verdict: SAFE · quality 75/100

None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours.

The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.

agentclicommand-line-toollinearlinearappllm

Quick Facts

Stars170
Forks18
LanguageTypeScript
CategoryAgent Tool
LicenseMIT
Quality Score75/100
Open Issues41
Last Updated2026-04-07
Created2025-09-02
Platformscli, node
Est. Tokens~58k

About linearis

Linearis CLI tool for Linear.app optimized for AI agents. JSON output, smart ID resolution, token-efficient usage commands, and a discover-then-act workflow that keeps agent context small. Works just as well for humans who prefer structured data on the command line. Why? The official Linear MCP works fine, but it eats up 13k tokens just by being connected -- before the agent does anything.

linearis alternative? Top 6 similar tools

Looking for a linearis alternative? If you're comparing linearis with other agent tool tools, these 6 projects are the closest alternatives on Agent Skills Hub — ranked by topic overlap, star count, and community traction.

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How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. It is a first-layer scan, not a manual audit — we say so rather than overstate it.

The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.

Sources & who's responsible:

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