Aggregate cross-verified evidence from multiple deep research engines into cited Markdown reports.
npx skills add https://github.com/ma08/botfiles --skill deep-research-ma08
Please help me install this Agent Skill. Skill: deep-research Source: https://github.com/ma08/botfiles/tree/main/codex/skills/deep-research Command: npx skills add https://github.com/ma08/botfiles --skill deep-research-ma08
High-stakes research questions require cross-checking evidence across multiple independent sources to avoid biased or incomplete conclusions, but manually coordinating multiple research tools and reconciling conflicting findings is time-consuming and error-prone. This Skill automates the entire end-to-end deep research workflow, from gathering evidence to synthesizing a reliable, cited report.
Use the deep-research skill to investigate the regulatory risks of launching a generative AI product in the EU and deliver a comprehensive citation-backed Markdown report.
High-intent search queries and answers about installing and using this skill.
To automate market analysis with citation-backed reports, you can use a multi-engine research workflow that queries OpenAI, Gemini, and Exa simultaneously, reconciles conflicting claims, and synthesizes findings into a structured Markdown report with explicit source citations and confidence levels.
The best way to conduct due diligence research across multiple sources is to run parallel queries against independent deep research engines, apply source quality triage to the evidence, and let an automated workflow resolve overlapping claims to produce decision-grade outputs for high-stakes questions.
Yes, you can use Exa and Gemini for deep research synthesis within a single parallel multi-engine execution workflow, aggregating cross-verified evidence alongside OpenAI to generate a reliable, standardized Markdown report with consistent citations.
Source conflict resolution works by applying source quality triage to evidence gathered from parallel multi-engine research, filtering overlapping claims from independent engines to improve conclusion confidence and ensure only corroborated data informs the final synthesis.
Yes, you need the Exa Python client installed to participate in the parallel multi-engine research execution, which is required to gather the cross-verified evidence used to synthesize the investment research Markdown reports.
Automated research synthesis for technical investigations is limited by the quality of evidence returned by the underlying research engines, requiring source quality triage and conflict resolution to prevent biased or incomplete conclusions from affecting the decision-grade output.
juanandresgsQuery OpenAI, Perplexity, and Gemini in parallel and synthesize comparative research reports.
iangcastill0Conduct citation-backed research across market, competitive, stock, and academic domains.
Probably-GroupSynthesize verified technical research claims from multiple providers with citations.
cuipengfeiCross-verify claims across multiple source categories with evidence labels.
