How does the Tech Decision skill gather data?

It utilizes parallel agents to scan your local codebase, official documentation, and community platforms like Reddit, Hacker News, and Dev.to simultaneously to ensure a comprehensive view.

What format are the final reports in?

The skill produces a structured Markdown report featuring an executive summary, a weighted scoring table, detailed pros and cons for each option, and a list of cited sources.

Can it analyze my specific project constraints?

Yes, it includes a codebase-explorer agent that identifies your existing patterns and technical limitations before making a recommendation.

Does it support comparing more than two technical options?

Absolutely. It can perform deep analysis on multiple competing options (A vs B vs C) and rank them based on custom evaluation criteria like performance, learning curve, and maintainability.

Tech Decision Architect

Name: Tech Decision Architect
Author: team-attention

byteam-attention

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313

Herramientas para Desarrolladores

Provides systematic, multi-source research and synthesized recommendations for complex technical and architectural choices.

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Tech Decision Architect is a specialized Claude Code skill designed to streamline the technical decision-making process for developers and architects. It automates the evaluation of libraries, frameworks, and architectural patterns by gathering intelligence from multiple sources—including your local codebase, official documentation, community forums like Reddit and Hacker News, and AI expert panels. By prioritizing an executive-summary-first approach, it helps teams quickly understand trade-offs, risks, and recommended paths forward, ensuring choices are backed by both data and project-specific context.

Características Principales

Parallel multi-source research across documentation, codebase, and community threads
Project-aware recommendations that consider existing technical constraints
Integration with dev-scan for real-world community sentiment
313 GitHub stars
Executive-summary-first reporting for rapid decision support
Automated trade-off analysis with weighted scoring systems

Casos de Uso

Evaluating complex architectural shifts such as Monolith to Microservices
Comparing competing libraries and frameworks like React vs. Vue or Prisma vs. TypeORM
Determining the best implementation strategy for features like WebSockets vs. Polling

Acerca de

Características Principales

Parallel multi-source research across documentation, codebase, and community threads
Project-aware recommendations that consider existing technical constraints
Integration with dev-scan for real-world community sentiment
313 GitHub stars
Executive-summary-first reporting for rapid decision support
Automated trade-off analysis with weighted scoring systems

Casos de Uso

Evaluating complex architectural shifts such as Monolith to Microservices
Comparing competing libraries and frameworks like React vs. Vue or Prisma vs. TypeORM
Determining the best implementation strategy for features like WebSockets vs. Polling