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lading-optimize-review

Coordinate five-persona peer reviews for lading optimization patches with benchmarks.

98|16|Updated Mar 3, 2021
Search Tags:#documentation#validation#optimization#review#benchmark#lading
One-click install
npx skills add https://github.com/DataDog/lading --skill lading-optimize-review
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: lading-optimize-review
Source: https://github.com/DataDog/lading/tree/main/.claude/skills/lading-optimize-review
Command: npx skills add https://github.com/DataDog/lading --skill lading-optimize-review

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes assets (resource) components.

What problem does it solve?

This Skill provides a formal framework for reviewing and validating optimization patches to lading. It ensures changes go through a deterministic, multi-persona evaluation process with mandatory benchmark data and logging into a central db.yaml.

Core Features & Use Cases

  • Five-persona review workflow: Duplicate Hunter, Skeptic, Conservative, Rust Expert, Greybeard collaborate to approve or reject optimizations.
  • Mandatory preflight and validation gates: Preflight checks, ci/validate, and measurement requirements are enforced.
  • Structured recording: All outcomes are recorded in assets/db.yaml and assets/db/ entries for traceability and learning.
  • Real-world use case: When optimizing a lading performance path, submit the patch for review with benchmark data to determine approval.

Quick Start

Run the review workflow to assess an optimization patch. For example: /lading-optimize-review

Frequently Asked Questions about lading-optimize-review

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I review lading optimization patches with benchmark validation?▼

Lading optimization patches are reviewed through a five-persona peer workflow that enforces preflight checks and mandatory benchmark data to validate changes before approval.

What is the five-persona review workflow for lading codebase optimizations?▼

The five-persona review for lading optimizations involves Duplicate Hunter, Skeptic, Conservative, Rust Expert, and Greybeard personas collaborating to rigorously evaluate and approve patches.

How do I record lading optimization review outcomes for traceability?▼

Recording lading optimization review outcomes requires logging structured results into assets/db.yaml and corresponding assets/db/ entries to ensure determinism and traceability.

Can I bypass preflight checks when submitting a lading optimization patch?▼

Preflight checks and ci/validate gates are mandatory for lading optimization patches, ensuring all changes are validated with benchmark data and cannot be bypassed.

Does lading optimization review require duplicate detection for patches?▼

Yes, duplicate detection is enforced during the lading optimization review process by the Duplicate Hunter persona to verify patch uniqueness and prevent redundant changes.

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