by linearis-oss · Agent Tool · ★ 264
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npm install -g linearisTaken from the project's README on GitHub.
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.
| Stars | 264 |
| Forks | 32 |
| Language | TypeScript |
| Category | Agent Tool |
| License | MIT |
| Quality Score | 75/100 |
| Open Issues | 8 |
| Last Updated | 2026-11-05 |
| Created | 2025-09-02 |
| Platforms | cli, node |
| Est. Tokens | ~16k |
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.
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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: