Evals for Linear

Linear's AI features ship behind brand promises about accuracy, safety, and reliability. Buyers and integrators need to know those promises hold up under adversarial prompts, edge-case workflows, and the long tail of real customer inputs — not just the demo path.

The Corsac eval library for Linear measures four dimensions teams care about most when deploying code assistant agents:

• Adversarial robustness — does the agent resist prompt injection, jailbreaks, and social-engineering attempts?
• Workflow quality— does it complete the task buyers were shown in the demo, on inputs that don't look like the demo?
• Safety gates — does it escalate or refuse when it should, and only then?
• Operator quality — does it preserve analyst trust by surfacing the right context at the right time?

Every eval pack above is hand-authored against Linear's public product surface and runnable in Corsac with your own data.