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Define backend-to-frontend delivery patterns for near-realtime vacancy analytics, freshness indicators, and streaming updates.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
SOC 직업 분류 기준
| name | realtime-analytics-api |
| description | Define backend-to-frontend delivery patterns for near-realtime vacancy analytics, freshness indicators, and streaming updates. |
| license | MIT |
| compatibility | opencode |
| metadata | {"audience":"frontend-and-backend-engineers","domain":"realtime-analytics"} |
Apply layer-specific quality checklists for Python ETL, Airflow DAGs, dbt models, SQL, FastAPI, Vue.js, and Docker Compose changes in the HH data platform.
Inspect git history and diffs to identify what changed, which platform layers are affected, and what risk signals to prioritise before applying review checklists.
Design small, maintainable Airflow DAGs with clear task boundaries, retry policy, and runtime assumptions.
Apply asyncio patterns for concurrent IO, background work, and coordinated refresh flows in Python analytics services.
Design dbt source, staging, and mart models with explicit schemas and clear layer responsibilities.
Break down a data-platform request into sequenced work items, dependencies, risks, and definition of done.
