godwinraj-ai/FastApply-MCP
🚀 Enhance code efficiency with FastApply MCP, an advanced platform for intelligent code analysis, search, and transformation tailored for modern teams.
🚀 Enhance code efficiency with FastApply MCP, an advanced platform for intelligent code analysis, search, and transformation tailored for modern teams.
npx skills add godwinraj-ai/FastApply-MCP🚀 Enhance code efficiency with FastApply MCP, an advanced platform for intelligent code analysis, search, and transformation tailored for modern teams.
Observal is an Observability and Evaluation platform for human-in-the-loop agents
Custom OpenClaw skills, hooks, and shell scripts for multi-agent ops automation. AI-authored with Claude Code.
Query and analyze data in Azure Data Explorer (Kusto/ADX) using KQL for log analytics, telemetry, and time series analysis. WHEN: KQL queries, Kusto database queries, Azure Data Explorer, ADX clusters, log analytics, time series data, IoT telemetry, anomaly detection.
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.
조사형 웹 크롤링과 문서 수집을 위한 유연한 자료수집 skill. 처음 보는 소스를 분석하고 수집 전략을 세운 뒤 HTML, JSON, PDF, 폼 요청, 쿠키, 단순 페이지네이션을 따라가며 재현 가능한 증거와 중간 스냅샷을 남겨야 할 때 사용한다.
A Claude Code plugin marketplace that codifies engineering craft: disciplined Python and data-engineering practice alongside deliberate session-knowledge workflows, packaged as reusable skills.