Aura (Agent Usage & Resource Analytics) : A local, Dockerized analytics pipeline designed to monitor, analyze, and replay local AI agent sessions (Claude Code, Gemini, etc.). The system decouples data extraction, transformation, and presentation to support both high-level BI reporting and granular, interactive session replays.
AURA is a Claude Code agent skill that aura (Agent Usage & Resource Analytics) : A local, Dockerized analytics pipeline designed to monitor, analyze, and replay local AI agent sessions (Claude Code, Gemini, etc.). The system decouples data extraction, transformation, and presentation to support both high-level BI reporting and granular, interactive session replays.
npx skills add darshanmeel/AURAInstalled? Explore more 研究与数据分析 skills: affaan-m/uspto-database, affaan-m/scholar-evaluation, affaan-m/literature-review · View all 6 →
Aura (Agent Usage & Resource Analytics) : A local, Dockerized analytics pipeline designed to monitor, analyze, and replay local AI agent sessions (Claude Code, Gemini, etc.). The system decouples data extraction, transformation, and presentation to support both high-level BI reporting and granular, interactive session replays.
Source: https://github.com/darshanmeel/AURA
Discovered during the daily awesomeskills.dev agent-skill hunt.
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.