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sauce

Run parallel searches across GitHub, startups, research, and communities to rank and save tech solutions.

Updated Apr 17, 2026
Search Tags:#web-search#tool-selection#rankings#parallel-queries#tech-evaluation#vendor-comparison#sauce
One-click install
npx skills add https://github.com/Aradotso/ara.engineer --skill sauce
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: sauce
Source: https://github.com/Aradotso/ara.engineer/tree/main/skills/sauce
Command: npx skills add https://github.com/Aradotso/ara.engineer --skill sauce

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Find best-in-class tech options for a given problem by running parallel searches across GitHub, startups, research, and community sources, then rank and save winners to a sauce list.

Core Features & Use Cases

  • Parallel searches across multiple sources to surface diverse options.
  • Ranking and curation of discoveries with a transparent scoring mechanism.
  • Sauce list persistence to track and reuse top picks for future decisions.
  • Use cases include technology stack selection, vendor comparison, and feature evaluation in fast-moving projects.

Quick Start

Provide a problem statement to Sauce and let it run parallel searches to compile and rank options.

Frequently Asked Questions about sauce

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

FAQPage Schema
How do I find and rank top tech solutions for a specific software problem?▼

To find and rank top tech solutions, provide a problem statement to run parallel searches across GitHub, startups, research, and community sources. It scores and ranks options based on relevance, maturity, traction, innovation, and ecosystem criteria.

How does parallel web search work for vendor comparison and tool evaluation?▼

Parallel web search for vendor comparison queries multiple sources simultaneously to surface diverse technology options. It then applies a transparent scoring mechanism to evaluate and rank tools for fast-moving projects.

Do I need web search tools to evaluate technology stacks and compile rankings?▼

Yes, you need access to web search results via Exa MCP tools to evaluate technology stacks. Structured prompts and scoring criteria are also required to compile evidence-backed rankings.

What is the best way to save and reuse top tech picks for future decisions?▼

The best way to save top tech picks is using a persistent sauce list. This feature tracks and stores ranked winners from your searches, allowing you to reuse curated options for future technology selection decisions.

Can I use this approach for feature evaluation in fast-moving software projects?▼

Yes, you can use this approach for feature evaluation in fast-moving projects. It conducts broad parallel searches and applies scoring criteria to deliver evidence-backed technology rankings quickly.

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