deep-research

To synthesize a cited research report, this skill uses a structured scoping phase, parallel source discovery via subagents, and triangulation to gather and evaluate multiple credible sources. It outputs a narrative report with inline citations and a sources appendix.

Triangulation in multi-source research is the process of cross-verifying information across multiple credible sources to ensure accuracy. It is needed for academic literature reviews, market analyses, and due diligence scenarios to present balanced perspectives and reduce bias.

Yes, you can use subagents for parallel source discovery in market analysis. The skill employs a phase-driven workflow where subagents independently discover sources, which are then triangulated and evaluated to support decision-making and industry evaluations.

Yes, this research methodology supports tiered depths including Quick, Standard, and Deep research. It applies a defined, repeatable phase methodology to handle both broad landscape surveys and focused deep-dives depending on your requirements.

To add credibility scoring and uncertainty notes to a literature review, the skill evaluates discovered sources and includes explicit source credibility scoring in the appendix. The final narrative report also contains explicit notes on data freshness and uncertainty.

You should not use an automated research agent for technology evaluations if your topic requires real-time data beyond the tool's access or if you need proprietary data behind strict paywalls, as the skill relies on discovering accessible credible sources and explicitly notes data freshness limitations.