Retrieve and validate multi-source evidence to build citation-backed research reports.
npx skills add https://github.com/lightxue/dotfiles --skill deep-research-lightxue
Please help me install this Agent Skill. Skill: deep-research Source: https://github.com/lightxue/dotfiles/tree/main/agent/skills/deep-research Command: npx skills add https://github.com/lightxue/dotfiles --skill deep-research-lightxue
Enterprise teams often need thorough, verifiable research that aggregates multiple sources, assesses credibility, and preserves provenance. This skill automates the end-to-end process, delivering citation-backed reports with structured pipelines and traceable evidence.
Trigger the skill with a research topic to start automatic, multi-source reporting.
High-intent search queries and answers about installing and using this skill.
Automatically generate a citation-backed research report by triggering the skill with a topic to initiate multi-source retrieval, credibility scoring, and progressive packaging into a structured document with a bibliography.
The best way to verify evidence and score source credibility is through automated validation that flags potential biases and performs DOI/URL validation across academic and technical sources during aggregation.
Yes, you can compile research findings with traceable provenance by applying parallel multi-source retrieval across web and academic platforms, producing a machine-readable trail linking conclusions to their original sources.
Structure an executive summary and synthesis by using progressive report packaging, which automatically builds these sections alongside findings and a complete bibliography as the evidence base is assembled.
Yes, multi-source retrieval preserves context for continuation, allowing you to pause and resume the automated compilation of verifiable citations and structured evidence without losing the gathered provenance trail.
Automated credibility scoring for verifiable citations relies on DOI/URL validation and bias flagging, meaning it may not fully capture nuanced contextual biases or evaluate sources behind inaccessible paywalls or non-standardized identifiers.
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