Research technical options and produce structured evaluation reports with recommendations.
npx skills add https://github.com/ys0714/ecom-agent --skill tech-researcher
Please help me install this Agent Skill. Skill: tech-researcher Source: https://github.com/ys0714/ecom-agent/tree/main/.claude/skills/tech-researcher Command: npx skills add https://github.com/ys0714/ecom-agent --skill tech-researcher
This Skill ensures engineering teams perform focused, evidence-backed technical research and solution reviews before implementation, preventing costly rework and design drift by surfacing open-source references, academic findings, and industry best practices aligned to the project's constraints.
Ask the tech-researcher to research "memory architecture for long-running conversational agents" and produce a 2-3 option comparison with a recommended approach, complexity estimate, and 3 clarification questions.
High-intent search queries and answers about installing and using this skill.
Evidence-based technical research for architecture decisions involves sourcing 3-5 references across open-source projects, industry posts, and academic papers, then synthesizing them into a comparative evaluation report to prevent design drift and rework.
The best way to compare technology selection options for e-commerce agent modules is to evaluate 2-3 viable solutions against project constraints, producing prioritized recommendations with implementation complexity, risks, and SPEC update instructions.
Yes, you can use this structured research pipeline for pre-implementation design reviews of memory architecture. It clarifies the problem, searches open-source and academic sources, and produces actionable recommendations tailored to long-running conversational agents.
To generate SPEC update instructions and clarification questions for a new recommendation algorithm, run a technical research review that mandates SPEC synchronization before coding and lists key uncertainties to resolve.
You need to source open-source references and academic papers when introducing a third-party vector DB to ensure validated options, surface trade-offs, and align industry best practices with your project's specific engineering constraints.
richardmbaileyAudits research proposals for novelty and validity before implementation.
VeronikaVashkevichExecutes project plans by managing tasks and tracking progress.
normcrandallAutomate end-to-end feature delivery from requirements to production-ready code.
zajcaConfigure golangci-lint with recommended Go linters for static analysis.
