What problem does it solve? Working a ServiceNow queue manually means juggling assigned incidents, SLA deadlines, and pending approvals across multiple screens, with the risk of breaching SLAs or approving requests without context. This Skill guides an AI through the snow-mcp tools to review, prioritize, and act on queue work in one conversation. ## Core Features & Use Cases - Queue Review and Prioritization: Pulls all assigned tasks via my_work, groups them by type and priority, and ranks them by SLA pressure using get_task_slas so anything past ~75% consumed surfaces first. - Approval Handling: Lists pending approvals with list_my_approvals, fetches the underlying record for context, then responds with respond_to_approval, enforcing comments on rejections. - Incident Conventions: Creates incidents with display names and impact/urgency-derived priority, distinguishes customer-visible comments from internal work notes, and resolves incidents through resolve_incident with proper close codes. - Use Case: Ask the AI to review your morning queue — it lists your incidents and CTASKs, flags two items nearing SLA breach, and walks you through approving a pending change request with full record context. ## Quick Start Review my ServiceNow queue, prioritize anything close to breaching its SLA, and help me respond to my pending approvals.
