Data & Analytics

Create, edit, or validate reproducible SQL or Python notebooks. Use for notebooks, SQL/Python scratchpads, reproducible exploration, audit trails, or runnable companions where the analysis should be reviewable or rerunnable.

Route Data Analytics plugin-level requests and broad analytics work to the right focused workflow. Use when Data Analytics is at-mentioned, or for analytics requests involving data, metrics, dashboards, reports, charts, notebooks, spreadsheets, KPIs, market sizing, or semantic layers.

Build polished analytical reports for executive, product, business, or technical audiences. Use when the task needs a durable answer-first narrative with evidence-backed findings, visuals or tables, caveats, and source context.

Build source-backed dashboards for monitoring performance, exploring drivers, or acting on product and business metrics. Use when the task needs a dashboard, scorecard, or monitoring view with clear metrics, filters, source definitions, and QA.

Assess whether structured data, query results, dashboards, or analytical evidence are trustworthy enough to use. Use when the task is to check data quality, reconcile conflicting sources or metric definitions, or decide whether evidence is safe to cite.

Create, edit, analyze, and verify standalone spreadsheet files or Google Sheets-ready workbooks, including .xlsx, .xls, .csv, and .tsv. Do not use for live controlling Microsoft Excel app or a live Excel session.

Create a spreadsheet using the Three-Statement Forecast template and its retained reference file. Use when the user selects or names Three-Statement Forecast. Build an integrated income statement, balance sheet, and cash flow forecast with assumptions, checks, and an executive summary.

Create a spreadsheet using the Sales Pipeline template and its retained reference file. Use when the user selects or names Sales Pipeline. Track opportunities, stages, owners, deal sizes, probabilities, forecasts, next steps, and risks.

Create a spreadsheet using the Financial Budget template and its retained reference file. Use when the user selects or names Financial Budget. Model actuals, budget and scenario forecasts, variances, cash runway, and departmental plans.

Create a spreadsheet using the Analytics Dashboard template and its retained reference file. Use when the user selects or names Analytics Dashboard. Monitor acquisition, engagement, retention, revenue, and conversion funnel KPIs with charts.

Apply best practices for Jupyter notebooks: cell ordering, reproducibility, parameterisation. Use when working with .ipynb files.

Apply best practices for Jupyter notebooks: cell ordering, reproducibility, parameterisation. Use when working with .ipynb files.

PyTorch for deep learning research and production

Data processing, ETL, and data pipeline patterns. Use when working with data transformation and analysis.

d3.js — data-driven document library for binding data to DOM, generating SVG visualizations, and creating interactive charts.

胶片漏光 + 颗粒噪点 + 16:9 letterbox + 衬线大字, 电影感开场 / 章节卡

SVG 曲线连接 + 便利贴节点 + 光标交互, 像白板 brainstorm

暖羊皮纸底 (#f5f4ed) + 墨蓝单色 accent (#1B365D) + 单一衬线字体, 编辑级排印

Bump version, commit, tag, and create a GitHub release

Graph analytics over a sparq RDF graph with the opt-in sparq-algos crate: project the graph onto a directed NodeGraph and run PageRank, centrality, k-core decomposition, community detection, and feature-gated directed strongly connected components, acyclicity checks, or topological sorting — all read directly from sparq-core's permutation indexes, deterministic, no model, no network. Use when ranking entities, measuring node cohesion, finding communities, classifying directed cycles, or order...

通过 `uvx mijiaAPI` CLI 控制米家智能设备。适用于：列出米家设备/家庭/场景/耗材、 获取或设置设备属性、执行设备动作、查询统计数据、运行场景、通过小爱音箱执行自然语言命令。 触发词包括"控制米家设备"、"米家"、"mijia"、"列出设备"、"设置亮度"、"打开灯"、 "执行动作"、"统计数据"、"耗电量"、"运行场景"、"小爱音箱"、"耗材"、"场景"。

Contract risk analysis, obligation mapping, and clause review. Use when the user asks to review, analyze, or check a contract or legal document.

Tabular and numerical data analysis with descriptive statistics and insights. Use when the user provides data, tables, CSVs, or numbers and wants analysis.

Expert data scientist for advanced analytics, machine learning, and statistical modeling. Handles complex data analysis, predictive modeling, and business intelligence.