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Found 1,899 Skills
Serve a quantized or unquantized LLM checkpoint as an OpenAI-compatible API endpoint using vLLM, SGLang, or TRT-LLM. Use when user says "deploy model", "serve model", "start vLLM server", "launch SGLang", "TRT-LLM deploy", "AutoDeploy", "benchmark throughput", "serve checkpoint", or needs an inference endpoint from a HuggingFace or ModelOpt-quantized checkpoint. Do NOT use for quantizing models (use ptq) or evaluating accuracy (use evaluation).
Build and organize a universe of potential acquirers for sell-side M&A processes. Identifies strategic and financial buyers, assesses fit, and prioritizes outreach. Use when preparing for a sell-side mandate, building a buyer universe, or evaluating potential partners. Triggers on "buyer list", "buyer universe", "potential acquirers", "who would buy this", "strategic buyers", or "financial sponsors".
How to build scenes: entry, dialogue, pacing, transitions. Use when writing or evaluating how scenes work on the page.
HK IPO Subscription Analysis — A "Four-Dimensional Evaluation" framework to diagnose whether Hong Kong new stocks are worth subscribing (Pricing Rationality / Issue Quality / Market Timing / Fundamental Outlook). Outputs three-tier ratings: Recommend / Neutral / Avoid, plus prospectus highlights, risk warnings, and subscription references. It is retail-investor friendly with conclusions upfront. Covers three scenarios: in-depth evaluation of a single new stock, browsing recent IPO subscription calendars, and judging whether to chase newly listed stocks after missing the subscription. Prioritizes data from Longbridge CLI (ipo detail / ipo subscriptions / ipo wait-listing / ipo listed / peer-comparison / news / quote / kline / index-quote, etc.); uses MCP fallback for data missing from CLI; uses WebSearch as a last resort for data still unavailable (prospectus TAM, original cornerstone announcement, claw-back ratio, grey market price, underwriter industry ranking). **The report must end with a fixed "Data Source Details" appendix**, where every figure can be traced to line number + capture time + period. Only covers Hong Kong Main Board and GEM; does not involve US / A-share IPOs; must actively prompt leverage risks when margin financing (孖展) is involved. Triggers: "打新", "港股打新", "新股申购", "新股申購", "新股", "打新分析", "新股分析", "招股", "招股书", "招股書", "基石投资者", "基石投資者", "国际配售", "國際配售", "公开发售", "公開發售", "暗盘", "暗盤", "回拨机制", "回撥機制", "孖展", "新股盈亏", "新股盈虧", "次新股", "破发", "破發", "中签率", "中籤率", "新股几手", "新股幾手", "新股值不值得打", "新股能不能打", "港股 IPO 推荐", "港股 IPO 推薦", "近期港股新股", "HK IPO analysis", "hong kong IPO worth it", "HK new listing", "cornerstone investor", "prospectus highlights", "grey market premium", "subscription ratio", "claw-back", "margin financing IPO", "0700.HK", "09988.HK", "01024.HK"
Assesses how ready a business is for AI adoption across six dimensions. Evaluates data maturity, tech stack, team skills, process documentation, budget, and culture. Generates a comprehensive ai-readiness-report.md with scores, gap analysis, and recommended starting points. Aligned with OneWave AI's audit methodology.
Run the full DEFT AOI improvement loop for NVIDIA TAO VisualChangeNet / ChangeNet PCB inspection models: baseline evaluate, RCA, ingestion of customer-supplied pre-generated AnomalyGen images, k-NN mining, retraining, and deployment gating until FAR / recall KPI targets are met. EA variant — does not run AnomalyGen inline; the customer pre-generates synthetic NG/OK pairs out-of-band and the loop ingests them. Use for prompts like "run the DEFT loop", "fine-tune until FAR below 0.1% at recall=100%", or "improve my AOI ChangeNet model with RCA and pre-generated synthetic defects"; do not use for standalone TAO training, one-off inference, generic anomaly generation, or RCA-only analysis.
QA-test a website or web app and return a 1-5 quality score (5 = flawless, 1 = broken) with evidence. Use when the user wants to test, QA, evaluate, score, or "check how good" a site, page, flow, or app — including a local dev server (e.g. "qa test localhost:5173", "does the checkout work?", "rate this landing page"). Drives a real Browser Use cloud browser, tunneling localhost automatically.
Assess organization's digital transformation readiness. Evaluate data culture, technology adoption, and process maturity.
Drives a disciplined explore → plan → implement → verify loop for changing an AI agent's behavior with confidence — whether fixing a reported failure or introducing a new requirement, business rule, or policy. Grounds the diagnosis in MLflow traces, codifies the desired behavior as a regression test suite (`mlflow.genai.evaluate` assertions in `@mlflow.test` pytest tests), and iterates the agent — not the test — until green, resisting quick system-prompt patches when the real fix is upstream (missing tool, retrieval source, or capability). Use whenever the user wants to fix or change how an agent behaves — e.g. "fix this issue in my agent", "this answer is wrong", "the agent is hallucinating", "improve my agent based on this trace", "make the agent do X instead of Y", "I want the agent to lead with/prioritize/recommend X", "new business rule: the agent should X", "always/never do X", "change the agent's default behavior" — or shares a trace they want addressed.
Senior Risk Management specialist for medical device companies implementing ISO 14971 risk management throughout product lifecycle. Provides risk analysis, risk evaluation, risk control, and post-production information analysis. Use for risk management planning, risk assessments, risk control verification, and risk management file maintenance.
Expert in Langfuse - the open-source LLM observability platform. Covers tracing, prompt management, evaluation, datasets, and integration with LangChain, LlamaIndex, and OpenAI. Essential for debugging, monitoring, and improving LLM applications in production. Use when: langfuse, llm observability, llm tracing, prompt management, llm evaluation.
Personal knowledge management for Obsidian combining GTD, Zettelkasten, and PARA. Six workflows: (1) Capture - "capture this", "remember this", "save this thought", "note this down" - saves thoughts/tasks to daily inbox without categorization; (2) Process inbox - "process my inbox", "organize captures", "GTD processing" - clarifies items and routes to projects or permanent notes; (3) Daily plan - "plan my day", "what should I work on", "morning planning" - creates prioritized task list based on energy and context; (4) Daily closeout - "daily closeout", "review my day", "evening reflection" - marks progress and drafts tomorrow's plan; (5) Setup - "set up my second brain", "configure vault" - configures vault path and user goals; (6) Excalidraw - "create a diagram", "visualize this", "draw flowchart", "sketch this" - creates .excalidraw.md files with rectangles, ellipses, diamonds, arrows, lines, and text. Proactively offers to capture valuable insights during research conversations.