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Found 776 Skills
Use when you need to implement or improve Java logging and observability — including selecting SLF4J with Logback/Log4j2, applying proper log levels (ERROR, WARN, INFO, DEBUG, TRACE), parameterized logging, secure logging without sensitive data exposure, environment-specific configuration, log aggregation and monitoring, or validating logging through tests. Part of the skills-for-java project
Universal deep research agent team. 13-agent pipeline for rigorous academic research on any topic. 7 modes: full research, quick brief, paper review, lit-review, fact-check, Socratic guided research dialogue, and systematic review with optional meta-analysis. Covers research question formulation, Socratic mentoring, methodology design, systematic literature search, source verification, cross-source synthesis, risk of bias assessment, meta-analysis, APA 7.0 report compilation, editorial review, devil's advocate challenges, ethics review, and post-research literature monitoring. Triggers on: research, deep research, literature review, systematic review, meta-analysis, PRISMA, evidence synthesis, fact-check, guide my research, help me think through, 研究, 深度研究, 文獻回顧, 文獻探討, 系統性回顧, 後設分析, 事實查核, 引導我的研究, 幫我釐清, 幫我想想, 我不確定要研究什麼, 研究方向, 研究主題.
You are an error tracking and observability expert specializing in implementing comprehensive error monitoring solutions. Set up error tracking systems, configure alerts, implement structured logging, and ensure teams can quickly identify and resolve production issues.
Use when building comprehensive monitoring and observability systems.
Orchestrate the complete advisor workflow for assembling and delivering a comprehensive financial plan, from data gathering through recommendations and ongoing monitoring. Use when the user asks about building a financial plan for a client, structuring a planning engagement, coordinating retirement and education and estate goals into one plan, running scenario analysis across a full financial picture, prioritizing competing recommendations, preparing for a plan presentation meeting, or deciding when a plan needs updating. Also trigger when users mention 'comprehensive financial plan', 'discovery meeting', 'cash flow analysis', 'retirement modeling', 'education funding gap', 'plan delivery', 'savings rate', 'plan update trigger', or 'is my client on track'.
Find and read academic papers: disambiguate queries, discover papers (search, citation traversal, recommendations, arXiv monitoring, trending, GitHub search), evaluate (TLDR, citations, code, SOTA), and read with structured analysis (3-level strategy). Use when: finding papers, reading a paper, related work, citation analysis, research trends, SOTA results, datasets. Do NOT use for generating literature survey reports (use research-survey), generating research ideas (use research-ideation), writing a paper's Related Work section (use paper-writing), comparing/ranking research ideas (use research-ideation), or planning paper structure (use paper-planning).
Discovers, enriches, and scores local businesses in any neighborhood using Nimble Web Search Agents (WSAs) and web data. Returns a structured, ranked list with confidence scores, reviews, social presence, and an interactive map. Use this skill when the user asks about local businesses, places, or neighborhood discovery. Common triggers: "find all coffee shops in", "map every bar in", "local businesses in", "discover gyms near", "what restaurants are in", "neighborhood guide for", "local places in", "find places near", "list all [business type] in [area]", "best [type] near [location]", "build a neighborhood guide", "local place search". Requires the Nimble CLI (nimble agent run, nimble search, nimble extract) for live web data via WSAs and fallback search. Do NOT use for competitor analysis or monitoring (use competitor-intel), company research or deep dives (use company-deep-dive), general web search or extraction (use nimble-web-expert).
Direct PubMed and NCBI E-utilities search workflows for biomedical literature, MeSH queries, PMID lookup, citation retrieval, and API-backed literature monitoring.
Post-investment monitoring via Longbridge Securities — tracks portfolio holdings vs plan on a quarterly / monthly basis, extracts key KPIs (revenue growth / gross margin / cash flow), flags deviations vs expectations, and generates a monitoring report with add / reduce / stop-loss recommendations. Triggers: "投后监控", "持仓监控", "定期复盘", "跟踪持仓", "持仓检视", "KPI跟踪", "业绩追踪", "投後監控", "持倉監控", "定期複盤", "追蹤持倉", "KPI追蹤", "post-investment monitoring", "position monitoring", "portfolio review", "KPI tracking", "performance tracking", "investment monitoring", "holding review".
World-class ML engineering skill for productionizing ML models, MLOps, and building scalable ML systems. Expertise in PyTorch, TensorFlow, model deployment, feature stores, model monitoring, and ML infrastructure. Includes LLM integration, fine-tuning, RAG systems, and agentic AI. Use when deploying ML models, building ML platforms, implementing MLOps, or integrating LLMs into production systems.
Monitor database performance and health. Use when setting up monitoring, analyzing metrics, or troubleshooting database issues.
Deploy and manage web apps using Azure App Service with auto-scaling, deployment slots, SSL/TLS, and monitoring. Use for hosting web applications on Azure.