Play 77
Research Paper AI
High✅ Ready
AI-powered academic research — literature review, citation analysis, and research gap identification.
AI-powered academic research assistant automating literature review, citation network analysis, methodology critique, and research gap identification. Azure AI Search indexes paper abstracts and full texts with semantic ranking, OpenAI analyzes methodology quality and identifies contradictions across studies, Microsoft Graph connects institutional knowledge bases, Cosmos DB stores citation networks and analysis results, and Functions orchestrate multi-paper analysis workflows.
Architecture Pattern
RAG + citation graph: paper ingestion → semantic search → methodology analysis → gap identification → synthesis
Azure Services
Azure OpenAIAzure AI SearchAzure Cosmos DBMicrosoft GraphAzure Functions
DevKit (.github Agentic OS)
- agent.md — root orchestrator with builder→reviewer→tuner handoffs
- 3 agents — Research Builder (gpt-4o), Reviewer (gpt-4o-mini), Tuner (gpt-4o-mini)
- 3 skills — deploy (217 lines), evaluate (126 lines), tune (236 lines)
- 4 prompts — /deploy, /test, /review, /evaluate with agent routing
- .vscode/mcp.json — FrootAI MCP with OpenAI + Semantic Scholar inputs + envFile
TuneKit (AI Config)
- config/openai.json — analysis and synthesis prompts
- config/research.json — citation databases, methodology frameworks, domain taxonomy
- config/guardrails.json — academic integrity, citation accuracy
- evaluation/eval.py — Citation accuracy >95%, Gap identification precision >80%
Tuning Parameters
Citation depthMethodology critique rigorDomain specializationSynthesis abstraction levelTime horizon for literature
Estimated Cost
Dev/Test
$60–150/mo
Production
$1K–4K/mo