AgentSkillsCN

sql-market-data

适用于量化研究、系统实施及生产管控的SQL市场数据工作流。当任务涉及查询正确性、索引策略，以及时间点一致性时，可选用此类工作流。

SKILL.md
--- frontmatter
name: sql-market-data
description: "SQL Market Data workflows for quantitative research, implementation, and production controls. use when tasks involve query correctness, indexing strategy, and point-in-time consistency."

SQL Market Data

objective

Execute sql market data work with reproducible research, explicit controls, and deployable outputs.

workflow

  1. •define source contracts, schema versions, and freshness objectives.
  2. •ingest data with replay support and deterministic normalization.
  3. •validate keys, timestamps, and point-in-time join behavior.
  4. •monitor quality metrics continuously and quarantine degraded feeds.
  5. •publish only when lineage, ownership, and quality thresholds are satisfied.

required diagnostics

  • •freshness, completeness, null-rate, and duplicate-rate trends.
  • •schema drift and breaking-change frequency across sources.
  • •point-in-time join integrity for features and labels.
  • •backfill and replay consistency versus canonical snapshots.
  • •predicate pushdown effectiveness and scan amplification
  • •point-in-time alignment for slowly changing dimensions

risk controls

  • •enforce hard thresholds for freshness and data-quality metrics.
  • •enforce quarantine and fallback paths for corrupted feeds.
  • •enforce full lineage metadata before downstream release.

outputs

  • •run python scripts/sql_market_data_diagnostics.py input.csv --output diagnostics.json and keep the json artifact.
  • •write an implementation memo using references/sql-market-data-playbook.md with assumptions, tests, limits, and rollout plan.

resources

  • •use scripts/sql_market_data_diagnostics.py for deterministic diagnostics.
  • •use references/sql-market-data-playbook.md for the domain-specific checklist and delivery structure.