8-phase literature-review pipeline. 7 federated sources, dedup, ranked retrieval, citation chasing, self-critique, 5 report archetypes.
npx skills add Agents365-ai/scholar-deep-research8-phase literature-review pipeline. 7 federated sources, dedup, ranked retrieval, citation chasing, self-critique, 5 report archetypes.
Source: https://github.com/Agents365-ai/scholar-deep-research
Discovered from GitHub repositories pushed in the last 24 hours for agent skills, Claude/Codex/Gemini workflows, MCP tooling, and adjacent AI-agent automation.
AskRally plugin for Claude Code — persona-based audience research via Rally's API
Write academic research documents following academic guidelines with peer-reviewed sources from Google Scholar and other academic databases. Always verify source credibility and generate IEEE standard references. Use for research papers, literature reviews, technical reports, theses, dissertations, conference papers, and academic proposals requiring proper citations and scholarly rigor.
Paper reader for non-academics. Reads a paper and tells it back as one continuous story — the life of the paper's core proposition (命题), told on a seven-beat spine (主角 / 困境 / 旧路 / 转折 / 解法 / 结局 / 内核): born in a bind on a base-rate ruler, crystallized as a bold conjecture, argued through mechanism and evidence, distilled into a new way of seeing, then walked out of the paper — life-tested and cashed into falsifiable predictions (检验). Output opens with a scannable 速读 card (一句话 / 大想法 / 只记三件事) that compresses the whole story three ways for the time-poor reader and the six-months-later self, then tells the full story. The job is storytelling that makes the paper land, not academic critique. Use when user shares an arxiv link, paper URL, PDF, or asks to analyze a research paper. Trigger words: '读论文', '讲论文', '把这篇讲给我听', '分析论文', 'paper', or when user shares an academic paper.
Automate Twelve Data tasks via Rube MCP (Composio). Always search tools first for current schemas.
The GPT-RAG Orchestrator service is an agentic orchestration layer built on Microsoft Foundry Agent Service and the Microsoft Agent framework. It enables agent-based RAG workflows by coordinating multiple specialized agents to collaboratively generate accurate, context-aware responses for complex user queries.
Multi-agent competitive intelligence platform. Any company URL → analyst-grade report in under 30s. Powered by Bright Data + Claude AI.