deep-research-analyst

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Expert guide for autonomous deep research, iterative web search, citation verification, evidence graph synthesis, and hallucination mitigation / Panduan ahli riset mendalam otonom, pencarian web iteratif, verifikasi sitasi, dan mitigasi halusinasi.

AI & Automation 51 stars 10 forks Updated today MIT

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Skill Content

# Deep Research Analyst (2026 Autonomous Research Edition) [English](#english) | [Bahasa Indonesia](#bahasa-indonesia) --- <a name="english"></a> ## English ### Orchestration & Integration Connects and orchestrates with relevant domain skills like `brainstorming`, `prd-architect`, `web-scraper`, `browser-automation-expert`, `project-context-mapper`, and `multi-agent-orchestration` to form an evidence-backed intelligence swarm. ### Description Production guide for architecting and executing autonomous **Deep Research** pipelines. Unlike simple one-shot retrieval (RAG), Deep Research operates as a goal-directed autonomous loop: decomposing queries into multi-perspective sub-questions, crawling and scraping academic/technical sources, scoring source credibility, cross-verifying facts across multiple independent citations, constructing an evidence graph, and synthesizing comprehensive, citation-grounded intelligence briefs. **Swarm Synergy:** Within the **Fan-Out / Fan-In Research Swarm**, this skill acts as the Lead Intelligence Subagent. It is deployed in Phase 1 (Discovery & PRD) to gather ground truth, audit competitor architectures, and resolve high-risk technical unknowns before code is written. ### Trigger Conditions - Requiring deep, multi-source investigation before architectural decision-making. - Benchmarking libraries, database engines, or cloud architectures with empirical data. - Building autonomous research agents, competitive intelligence scrapers, or liter...

Details

Author
roedyrustam
Repository
roedyrustam/vibes-plug
Created
3 months ago
Last Updated
today
Language
Python
License
MIT

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