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/AURAAura (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.
Installable Agent Skills for Scholar Sidekick — turn DOI/PMID/ISBN/arXiv/ISSN/ADS/WHO IRIS into citations (10,000+ CSL styles), exports (BibTeX/RIS/EndNote/CSV), and retraction / open-access / fabrication checks. Zero-install REST skill + MCP skill.
LLM-assisted research wiki system with Claude Code skills, agents, and clo-author template
Agent skill repository discovered by 10x-chat research.
Automate Spotify music playback, playlist management, and audio analysis workflows
Generate text-to-video with HappyHorse 1.0 on RunComfy. Documents HappyHorse 1.0's strengths (#1 on Artificial Analysis Video Arena, native 1080p with in-pass synchronized audio, multi-shot character consistency, 6-language prompt support), the duration / aspect-ratio / resolution schema, and when to route to Wan 2.7 / Seedance 2 / LTX 2 instead. Calls `runcomfy run happyhorse/happyhorse-1-0/text-to-video` through the local RunComfy CLI. Triggers on "happyhorse", "happy horse", "happyhorse 1.0", "happyhorse video", or any explicit ask to generate video with this model.
Rigor Reproduce compatible skill slug for README-first deep learning repository reproduction. Use when the user wants an end-to-end, minimal-trustworthy flow that reads the repository first, selects the smallest documented inference or evaluation target, coordinates intake, setup, trusted execution, optional trusted training, optional repository analysis, and optional paper-gap resolution, enforces conservative patch rules, records evidence assumptions deviations and human decision points, and writes the standardized `repro_outputs/` bundle. Do not use for paper summary, generic environment setup, isolated repo scanning, standalone command execution, silent protocol changes, score chasing, or broad research assistance outside repository-grounded reproduction.