skills/kentoshimizu/sw-agent-skills/ml-feature-engineering

ml-feature-engineering

SKILL.md

Ml Feature Engineering

Overview

Use this skill to design features that are useful, explainable, and consistent across training and serving.

Scope Boundaries

  • Use this skill when the task matches the trigger condition described in description.
  • Do not use this skill when the primary task falls outside this skill's domain.

Shared References

  • Online/offline parity rules:
    • references/online-offline-parity-rules.md

Templates And Assets

  • Feature specification template:
    • assets/feature-spec-template.csv

Inputs To Gather

  • Candidate feature hypotheses and business rationale.
  • Data sources and freshness constraints.
  • Serving path capabilities and latency budget.
  • Leakage/fairness/compliance constraints.

Deliverables

  • Feature catalog with lineage and ownership.
  • Parity validation plan for train vs serve paths.
  • Feature risk and maintenance notes.

Workflow

  1. Define feature specs in assets/feature-spec-template.csv.
  2. Validate parity assumptions with references/online-offline-parity-rules.md.
  3. Prioritize features by incremental value vs complexity.
  4. Verify leakage and freshness assumptions.
  5. Publish feature rollout and deprecation plan.

Quality Standard

  • Feature definitions are versioned and reproducible.
  • Online/offline behavior is consistent for decision-critical features.
  • Feature ownership and monitoring are explicit.

Failure Conditions

  • Stop when feature logic diverges between training and serving.
  • Stop when feature value cannot justify operational complexity.
  • Escalate when parity gaps remain unresolved.
Weekly Installs
4
GitHub Stars
4
First Seen
Feb 28, 2026
Installed on
opencode4
gemini-cli4
codebuddy4
github-copilot4
codex4
kimi-cli4