数据与 AI技能

Coordinate a cross-session or cross-machine handoff — snapshot the open work, write a status doc to the pulp-planning repo on main, and emit a ready-to-paste goal prompt that links it, so a fresh session (often on another machine) can pick up and finish. Use when the user says "coordinate a handoff", "hand this off", "move this work to a new machine", "we're retiring this session", or asks for a status doc plus a goal for someone else to continue.

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Convert any pile of documents (PDF, Word, HTML pages, wiki exports, PowerPoint slides) into clean, LLM-ready markdown context: inventories the sources, picks the right extractor per file type (pdftotext or PyMuPDF for PDF, pandoc or mammoth for docx, readability extraction for HTML.

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Build a production-ready data API from scratch: scaffold REST endpoints with models and validation, generate integration tests that verify every route, then load test for scalability. Use when you need an API backend, data service, CRUD layer, or microservice with verified correctness and performance.

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Audit game analytics and telemetry implementation -- event tracking completeness, FTUE and monetization funnel coverage, retention metric infrastructure, A/B testing framework, heatmap data collection, churn prediction signals, and LTV modeling support..

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Audit research data management infrastructure -- score FAIR principles compliance (Findable, Accessible, Interoperable, Reusable) across all sub-principles, evaluate data governance frameworks and lifecycle management, assess metadata schema quality (Dublin Core, DataCite, DDI.

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Analyze retail merchandising systems including planogram optimization (space-to-sales alignment, fair share index, sales per linear foot), visual merchandising effectiveness for in-store displays and e-commerce product pages, market basket analysis with association rule mining (Apriori.

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Generate a production-grade OEE (Overall Equipment Effectiveness) measurement pipeline for a manufacturing line — data ingestion from MQTT/OPC-UA/Modbus/CSV, A×P×Q calculation engine, Six Big Losses categorizer, MTBF/MTTR/TEEP metrics, Grafana or Streamlit dashboard.

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Pull and analyze Google Search Console data via the GSC API. Produces: weekly query × page performance with WoW/MoM/YoY deltas, top movers report (winners + losers ranked by absolute click change), click-loss attribution (lost rank? Triggers: "GSC", "Google Search Console".

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Analyze program impact measurement software for logic model completeness, indicator tracking rigor, data collection methodology, causal attribution modeling, cost-effectiveness analysis, beneficiary feedback integration, and funder reporting accuracy..

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Analyze mobile app analytics implementation including event tracking completeness and naming conventions, SDK configuration audit (Firebase Analytics, Amplitude, Mixpanel, PostHog), attribution tracking with AppsFlyer/Adjust/Branch and SKAdNetwork conversion values.

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Build the internal link graph for a site, run PageRank-style authority distribution, detect orphan pages, and recommend new internal links via embedding-based semantic similarity (not keyword matching)..

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Evaluate elder care fall risk prediction systems including wearable sensor integration, gait and balance analytics, risk scoring algorithms, environmental hazard detection, medication interaction flagging, mobility trend tracking, and alert/response workflow effectiveness.

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Analyze disaster prediction and early warning systems — model accuracy for flood, earthquake, wildfire, hurricane, and tsunami hazards, data pipeline reliability from sensor networks and satellite feeds, alert distribution latency and channel coverage.

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Review clinical data models and APIs for HL7 FHIR conformance, terminology standards, interoperability, and clinical workflow correctness. Triggers: 'check FHIR compliance', 'review clinical data model', 'audit HL7 conformance', 'validate medical terminology codes'.

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Analyzes apparel demand prediction systems for trend forecasting, size curve optimization, color and style analytics, sell-through rate tracking, and markdown optimization following CPFR collaborative planning and GTIN product identification standards..

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Design and analyze engineering experiments or simulations using baseline cases, hypothesis-driven DOE, traceable data processing, defensible plots, uncertainty, and validation. Use for CFD, laboratory data, ML workflows, parameter studies, or research code.

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Iterative manuscript improvement workflow where a reviewer agent critiques, an author agent revises, a verifier checks the revision, and the loop repeats until acceptance or a human-pause condition is reached. Use for virtual peer review, reviewer-author revision loops, rebuttal preparation, resubmission polishing, journal paper improvement, response-to-reviewers drafting, and deciding when additional data, experiments, theory, modeling, or author judgment is required before further revision.

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Fetch the latest AI/ML news, trending open-source projects, social media discussions, and KOL (Key Opinion Leader) perspectives from 370+ curated sources. Use when the user asks about recent AI news, AI trends, what's happening in machine learning, open-source AI projects, AI Twitter/Reddit discussions, or wants a daily AI briefing.

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Parse natural-language quantities, units, dates, and ranges ("5'11\"", "1.5 cups", "72 in to cm", "three days ago", "between 5 and 10 kg", "it's hot") into canonical, validated values with issue codes and spans — and humanize them back. Use when a form input, LLM tool schema, MCP handler, or import pipeline takes free-text measurements/units/dates. Covers Standard Schema fields (quantityField/dateField/lingoObject) for the AI SDK and MCP, the headless <lingo-input>, unit conversion, and format/humanize round-trips. Zero-dependency TypeScript, deterministic.

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AI工程师角色。关键词：AI/LLM/智能体/Prompt/上下文工程/多智能体/工作流/RAG/Function Call/效果评测。激活后设计提示词、构建智能体调用链、评测输出质量。

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后端开发角色。关键词：后端/FastAPI/Python/API接口/数据库/PostgreSQL/业务逻辑/认证/SSE。激活后读技术架构.md，按四层架构实现，写完任何DB函数必须立即集成测试。

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根据当前科研数字分身状态，生成结构化提示词，供用户提交给 ChatGPT 等带记忆功能的 AI，从中提取与画像构建相关的信息。不询问用户使用哪个 AI 工具，提示词对所有平台通用。

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Craft high-quality natural-language image prompts for any modern text-to-image or image-edit model that accepts flowing English. Trigger when the user wants help writing, rewriting, improving, or translating an English natural-language image prompt — including "write me an image prompt", "improve this image prompt", "describe this scene for an image model", or "convert these tags into a natural language prompt". Do NOT trigger for requests that are purely about dispatching to an image API, choosing samplers/schedulers, picking LoRAs, or setting up ControlNet — those belong to a runtime skill.

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用于实现或审查前端服务端状态流程：类型化查询、请求缓存、失效、mutation、乐观更新、无限查询、预取、SSR hydration 或 API 层整合。不要用于本地 UI 状态或 Service Worker 缓存；中文触发词包括 数据获取、缓存、乐观更新。

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