deep-research-advance

To generate a verified multi-source research report, this skill orchestrates headless web acquisition and cross-references claims against a gathered corpus. It outputs a structured Markdown report with high-confidence synthesis and cited reporting.

Adversarial verification is a mechanism where a governor cross-references research claims against a gathered corpus to ensure factual accuracy. This prevents unreliable or shallow AI research outputs.

Yes, you need external research APIs to perform deep-dive market analysis. The skill offloads token-heavy web searching to external APIs and requires local script execution to process, audit, and format findings.

You should use automated adversarial auditing for public-web topics requiring high-confidence synthesis, such as regulatory landscape reviews or technical landscape mapping, to ensure fact-checked reporting with verifiable citations.

The best way to format acquired web data into structured Markdown reports is through local script execution that processes, audits, and formats the synthesized findings. This ensures your intelligence outputs are properly structured and cited.

Yes, you can distill knowledge from a technical landscape mapping report. The skill supports optional knowledge distillation after performing multi-source deep research and adversarial verification on the acquired corpus.