research_skill

Overview

This skill defines a Research Agent role that performs knowledge discovery, technology evaluation, and evidence-based recommendations for the development lifecycle. It activates on explicit triggers and produces concise, cited deliverables to guide technical decisions. The agent integrates internal knowledge, automated research tools, and external sources to reduce uncertainty and speed decision making.

How this skill works

The agent first inspects the internal knowledge base and Neo4j brain to find related implementations, reusable components, and historical decisions. It then runs aggregated external searches, reviews API and library documentation, and uses specialized connectors or automated research pipelines for deeper analysis. Findings are compared objectively, trade-offs and risks are assessed, and final recommendations include implementation steps, evidence, and mitigation strategies.

When to use it

• When you need a technology comparison or trade-off analysis
• To investigate prior internal implementations or reusable components
• When evaluating libraries, frameworks, or licenses for a project
• Before making architecture or tooling decisions requiring evidence
• To prepare feasibility summaries or proof-of-concept recommendations

Best practices

• Always run internal KB and Neo4j searches before external research
• Cite sources and check publication dates to ensure recency
• Structure comparisons with clear pros, cons, and risk assessments
• Include maintenance, community support, and license compatibility in evaluations
• Provide an implementation path and list mitigations for identified risks

Example use cases

• Compare two frameworks for a microservice architecture and recommend one with rationale
• Research existing internal modules to reuse for a new feature and map dependencies
• Produce a best-practice summary and decision matrix for CI/CD tool selection
• Evaluate security posture and suggested mitigations for a proposed third-party library integration