What problem does it solve? When a Batch API job is stuck, results are payment-blocked, usage is missing, or submission fails, engineers need a systematic way to trace the job through ingress, acceptance, submission, provider polling, finalization, billing, and results serving instead of guessing across scattered logs. ## Core Features & Use Cases - Lifecycle Tracing: Reconstructs an evidence-backed timeline for any batch job using Datadog log queries keyed by job ID, entity ID, trace ID, or symptom. - Symptom Decision Table: Maps symptoms like "batch stuck", "results 402", or "usage missing" to the correct lifecycle stage, queries, and likely causes. - GCS Artifact Inspection: Compares raw provider responses against materialized results in Google Cloud Storage to pinpoint parse and render failures. - Use Case: A customer reports their batch finished but results return HTTP 402. Use this Skill to query the payment-gate events, determine whether settlement is pending or explicitly blocked, and produce a root-cause report with a shareable Log Explorer URL. ## Quick Start Ask the AI to investigate why batch job batch-1785263765-XPvEnZuifmN37sHaJ9pm is stuck and produce a root-cause timeline.