What problem does it solve? Writing correct Logging Query Language (LQL) queries for Google Cloud Logging requires knowing exact resource types, log IDs, and payload schemas that vary per service. This Skill converts natural language debugging or auditing requests into syntactically correct LQL queries, avoiding common mistakes like wrong resource types or invalid operators. ## Core Features & Use Cases - Natural language to LQL conversion: Produces raw, ready-to-paste LQL queries with correct syntax rules (double quotes, uppercase boolean operators, explicit parentheses). - Service-specific schemas: Ships reference files for 20+ Google Cloud services including GKE, Compute Engine, BigQuery, Cloud Run, Cloud SQL, IAM, and audit logs, ensuring accurate resource.type and log_id values. - Safe placeholder handling: Omits non-essential filters when identifiers are missing and inserts angle-bracket placeholders only for strictly required variables. - Use Case: Ask for "error logs from my Cloud Run service yesterday" or "who deleted my GCE instance" and receive a precise query targeting the right resource type, log ID, and protoPayload fields. ## Quick Start Ask the assistant to generate a Cloud Logging query for your scenario, for example: write an LQL query that finds all 5xx errors from my App Engine service in the last 24 hours.
