全部能力

Oracle Database guidance for SQL, PL/SQL, SQLcl, ORDS, administration, app development, performance, security, migrations, and agent-safe database workflows.…

Expert marketing analytics covering campaign analysis, attribution modeling, marketing mix modeling, ROI measurement, and performance reporting. Use when analyzing campaign ROI, comparing attribution models, optimizing marketing budget allocation, building executive dashboards, or running A/B test statistical analysis.

Neuropixels neural recording analysis. Load SpikeGLX/OpenEphys data, preprocess, motion correction, Kilosort4 spike sorting, quality metrics, Allen/IBL…

Microscopy data management platform. Access images via Python, retrieve datasets, analyze pixels, manage ROIs/annotations, batch processing, for high-content…

Quarterly / monthly financial report — masthead with KPIs, revenue and burn charts, P&L summary table, top-line highlights, and an outlook paragraph. Use when the brief mentions "financial report", "Q3 report", "MRR review", "P&L", or "财报".

Use when defining product KPIs, building metric dashboards, running cohort or retention analysis, or interpreting feature adoption trends across product stages.

Expert sales operations covering CRM management, sales analytics, territory planning, compensation design, and process optimization. Use when building pipeline reports, designing territories, setting quotas, creating comp plans, or auditing CRM data quality.

Analyze SaaS company valuation compression between funding rounds. Use this skill whenever the user asks about: how much a SaaS company's valuation multiple changed between rounds, why the ARR multiple compressed or expanded, comparing a company's compression to macro benchmarks, or explaining what drove valuation changes for any VC-backed software company. Trigger on phrases like "valuation compression", "ARR multiple", "round-to-round valuation", "multiple change", or when the user asks to compare a company's funding rounds. Always use this skill for any multi-round SaaS valuation analysis — do not try to answer from memory alone.

A consumer-feeling dating / matchmaking dashboard — left rail navigation, ticker bar of community signals, headline KPIs, a 30-day mutual-matches bar chart, and a match-rate trend block. Editorial typography, restrained accent. Use when the brief asks for a "dating site", "matchmaking", "community dashboard", "social network dashboard", or any consumer product where the data is the story.

Neuropixels neural recording analysis. Load SpikeGLX/OpenEphys data, preprocess, motion correction, Kilosort4 spike sorting, quality metrics, Allen/IBL…

Python interface to OpenMS for mass spectrometry data analysis. Use for LC-MS/MS proteomics and metabolomics workflows including file handling (mzML, mzXML,…

MDV — Markdown superset for documents, dashboards, and slides with embedded charts, KPI stats, and data visualizations exported to HTML or PDF.

Advanced Scrum Master skill for data-driven agile team analysis and coaching. Use when the user asks about sprint planning, velocity tracking, retrospectives,…

Exports Amazon RDS or Aurora database snapshots to Amazon S3 in Apache Parquet format for analytics, backup, or data migration. Handles snapshot selection or…

Local execution tools for Instagram hosted collection workflows, including actor runs, dataset normalization, ranking, comment clustering, and watchlist…

订阅 AI 和技术类 RSS 订阅源，并使用成熟的 Python 工具（feedparser + sqlite3）将规范化后的元数据持久化存储到 SQLite。在添加订阅源时使用……

Data analysis, visualization, and storytelling skill for financial and RevOps contexts. Use when: analyzing revenue data, building forecasts, cohort analysis, churn modeling, pipeline analytics, creating data-driven reports, building dashboards, cleaning messy data, sanity-checking analytical claims, exporting to Excel with formulas, or extracting data from PDFs. Features decision logging, bias-aware interpretation, and progressive disclosure (slide deck -> detailed report -> full notebook with all decisions documented).

Transform raw data from CSVs, Google Sheets, or databases into executive-ready reports with visualizations, key metrics, trend analysis, and actionable…

Grafana Cloud infrastructure monitoring — Kubernetes monitoring, cloud provider integrations (AWS, Azure, GCP), host and container monitoring, infrastructure dashboards, and collector setup. Use when setting up Kubernetes monitoring, connecting cloud provider metrics, configuring node exporter or cAdvisor, setting up infrastructure dashboards, or using the k8s-monitoring Helm chart.

Grafana Cloud Database Observability — query-level performance insights for MySQL and PostgreSQL. Covers setup with Grafana Alloy, query samples, visual explain plans, RED metrics, pg_stat_statements and Performance Schema integration, and correlation with application traces. Use when monitoring database performance, diagnosing slow queries, setting up database observability for MySQL or PostgreSQL (self-managed, RDS, Aurora, Azure, Cloud SQL), or correlating DB metrics with APM data.