tech-stack-evaluator

What This Skill Does

The tech-stack-evaluator is a powerful analytical engine designed to provide data-driven insights for engineering decisions. It bridges the gap between high-level architectural requirements and granular technical trade-offs. By processing natural language, YAML, or JSON inputs, it generates weighted comparisons, long-term financial forecasts, and ecosystem health scores. This skill empowers teams to move beyond subjective opinions, offering quantitative backing for choosing specific frameworks, cloud providers, or database solutions based on organizational priorities like developer velocity, cost containment, or long-term maintainability.

Installation

To integrate this skill into your OpenClaw environment, execute the following command in your terminal: clawhub install openclaw/skills/skills/alirezarezvani/tech-stack-evaluator

Ensure that your OpenClaw agent has the appropriate permissions for data processing if you intend to run the associated Python analysis scripts locally, as some components rely on fetching external metadata from sources like GitHub or npm registries.

Use Cases

• Architectural Selection: Evaluating the viability of frontend frameworks or backend runtimes for new projects.
• Budget Forecasting: Projecting 3-5 year TCO for infrastructure and hosting costs including hidden operational overhead.
• Risk Mitigation: Assessing the security posture and maintenance frequency of third-party dependencies before adoption.
• Legacy Modernization: Estimating the engineering effort required to migrate monolithic legacy applications to modern microservices or serverless architectures.

Example Prompts

1. "Compare PostgreSQL vs MongoDB for a high-concurrency e-commerce application. Focus on consistency, scalability, and developer experience weights of 40/30/30."
2. "Calculate the 5-year TCO for hosting a Next.js application on AWS Fargate versus Vercel, assuming a 50% yearly traffic growth and a team of 10 engineers."
3. "Evaluate the migration risk of moving from a legacy Express.js setup to NestJS. Provide an effort estimate for a 100k line codebase with a team of 5."

Tips & Limitations

To maximize the quality of the output, always provide clear weightings for your priorities. If you do not specify weights, the skill will default to a general-purpose evaluation that may not align with your specific constraints. Be aware that ecosystem health scoring relies on real-time external data; therefore, ensure network connectivity is enabled for the agent. Finally, while the TCO analysis is highly detailed, remember that it provides estimates based on industry benchmarks—always validate financial projections against your actual cloud billing logs and internal labor costs.