AgentSkillsCN

feed-handler-normalization

适用于量化研究、系统实施及生产管控的馈送处理器归一化工作流。当任务涉及生产交易系统中的馈送与处理器相关工作流时，可选用此类工作流。

SKILL.md
--- frontmatter
name: feed-handler-normalization
description: "Feed Handler Normalization workflows for quantitative research, implementation, and production controls. use when tasks involve feed and handler workflows in production trading systems."

Feed Handler Normalization

objective

Execute feed handler normalization 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.

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/feed_handler_normalization_diagnostics.py input.csv --output diagnostics.json and keep the json artifact.
  • •write an implementation memo using references/feed-handler-normalization-playbook.md with assumptions, tests, limits, and rollout plan.

resources

  • •use scripts/feed_handler_normalization_diagnostics.py for deterministic diagnostics.
  • •use references/feed-handler-normalization-playbook.md for the domain-specific checklist and delivery structure.