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DavidLam-oss
DavidLam-ossCOMMUNITY
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openprd-benchmark-router

Routes AI product development tasks to relevant benchmarks and design sources.

283|45|Updated Jan 25, 2026
Search Tags:#research#benchmarking#product-design#context-engineering#prompt-engineering#agent-harness
One-click install
npx skills add https://github.com/DavidLam-oss/obsidian-wechat-converter --skill openprd-benchmark-router
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: openprd-benchmark-router
Source: https://github.com/DavidLam-oss/obsidian-wechat-converter/tree/main/.claude/skills/openprd-benchmark-router
Command: npx skills add https://github.com/DavidLam-oss/obsidian-wechat-converter --skill openprd-benchmark-router

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill solves the challenge of finding high-quality, relevant benchmarks and design references for complex AI product development, preventing the common pitfalls of aimless searching or over-reliance on generic advice.

Core Features & Use Cases

  • Context-Aware Routing: Identifies the specific domain of your task—whether it is CLI design, Agent harness engineering, or PR review workflows—and routes you to the most relevant evidence.
  • Evidence-Based Design: Provides a structured approach to evaluating external sources, ensuring you extract actionable design principles rather than just copying surface-level features.
  • Use Case: When building a new AI code review harness, use this Skill to identify the most relevant research papers and industry-standard implementations to inform your architecture.

Quick Start

Use the openprd-benchmark-router skill to find the best architectural references for designing a long-running agent harness.

Frequently Asked Questions about openprd-benchmark-router

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

FAQPage Schema
How do I find relevant benchmarks for designing an AI agent harness?▼

To find relevant benchmarks for agent harness design, use context-aware routing to identify your specific domain and route you to verified research papers and industry-standard implementations.

What is evidence-based design for AI product development?▼

Evidence-based design for AI product development is a structured approach to evaluating external sources, ensuring you extract actionable design principles rather than copying surface-level features.

How do I evaluate research papers for CLI optimization and product design?▼

Evaluate research papers for CLI optimization by applying a structured benchmarking framework that prioritizes verified sources and minimizes irrelevant context expansion during technical implementation.

When do I need a structured benchmarking framework for AI products?▼

You need a structured benchmarking framework when making evidence-based architectural decisions, preventing aimless searching and over-reliance on generic advice during complex AI product development.

Does this benchmarking router work for PR review workflows and context engineering?▼

Yes, the benchmarking router identifies specific domains like PR review workflows and context engineering, applying structured routing to find the most relevant technical evidence for your task.

What is the best way to avoid irrelevant context expansion during prompt engineering research?▼

The best way to avoid irrelevant context expansion during prompt engineering research is to use precision-guided routing that prioritizes verified sources for evidence-based decision-making.

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