MOSAIC—模組化優化與搜尋代理框架 是做什麼的？
一個受 AutoKaggle 啟發、專為自主數據科學競賽設計的多代理框架。
一個受 AutoKaggle 啟發、專為自主數據科學競賽設計的多代理框架。
MOSAIC 是一個模組化的多代理框架，靈感來自 AutoKaggle，旨在讓 AI 代理能自主參與數據科學競賽。它將複雜的數據科學工作流程拆分為一系列可組合的模組，每個模組由專門的代理處理，並透過優化與搜尋策略協同合作。此技能支援在 Claude Code、Cursor、Codex 等開發環境中運行，為數據科學任務提供結構化且可擴展的解決方案。開發者可以利用 MOSAIC 自動化數據預處理、特徵工程、模型選擇與超參數調優等步驟，從而專注於更高層次的策略決策。
npx skills add GetIT-Sunday/MOSAIC-Modular-Optimization-and-Search-for-Agentic-Intelligence-in-CompetitionsInstalled? Explore more 研究與資料分析 skills: affaan-m/uspto-database, affaan-m/scholar-evaluation, affaan-m/literature-review · View all 6 →
一個受 AutoKaggle 啟發、專為自主數據科學競賽設計的多代理框架。
USPTO patent and trademark data workflow for official record lookup, PatentSearch queries, TSDR checks, assignment data, and reproducible IP research logs.
Structured scholarly-work evaluation for papers, proposals, literature reviews, methods sections, evidence quality, citation support, and research-writing feedback.
Systematic literature-review workflow for academic, biomedical, technical, and scientific topics, including search planning, source screening, synthesis, citation checks, and evidence logging.
The agent harness performance optimization system. Skills, instincts, memory, security, and research-first development for Claude Code, Codex, Opencode, Cursor and beyond.
Agent skill repository discovered by 10x-chat research.
Review backend code for quality, security, maintainability, and best practices based on established checklist rules. Use when the user requests a review, analysis, or improvement of backend files (e.g., `.py`) under the `api/` directory. Do NOT use for frontend files (e.g., `.tsx`, `.ts`, `.js`). Supports pending-change review, code snippets review, and file-focused review.