deep-research

Generating a cited Markdown research report requires providing a topic, which the skill decomposes into a structured outline, drafts with evidence-backed data-pool sourcing, and formats with traceable citations. It outputs a fact-checked Markdown document.

To ensure your industry analysis passes automated QA and style-lint checks, this skill integrates quality assurance directly into the drafting process. It applies citation formatting, style guidelines, and error-checking to produce a rigorous Markdown report.

You can use this for deep research tasks requiring counterpoints and fact-checking because it applies automated chapter drafting with error-checking and counterpoint integration. It translates complex topics into structured, evidence-backed Markdown reports.

This approach supports evidence-backed data collection with transparent sourcing by generating a data-pool during the research phase. It structures your topic, collects verifiable data, and outputs a cited Markdown report designed to pass citation-lint checks.

A limitation of using automated QA for structured research reports is that it relies on the underlying data-pool quality and style-lint configurations. While it ensures citation formatting and structural rigor, it cannot verify external source truthfulness beyond the provided evidence.