Technical Skills

Helps you work with Palantir Foundry using the pltr CLI. Use this when you need to query datasets, manage orchestration builds, work with ontologies, run SQL queries, manage folders/spaces/projects, copy datasets, or perform admin operations in Foundry. Triggers: Foundry, pltr, dataset, SQL query, ontology, build, schedule, RID.

Testing framework for evaluating Databricks skills. Use when building test cases for skills, running skill evaluations, comparing skill versions, or creating ground truth datasets with the Generate-Review-Promote (GRP) pipeline. Triggers include "test skill", "evaluate skill", "skill regression", "ground truth", "GRP pipeline", "skill quality", and "skill metrics".

Generate interactive HTML visualizations of the skills collection, codebase structure, or dependency graphs. Uses D3.js for interactive visualization with collapsible nodes, color-coded categories, and hover details. Triggers on "visualize skills", "generate skill map", "codebase visualization", or "show skill dependencies".

Evaluates machine learning models for performance, fairness, and reliability using appropriate metrics and validation techniques. Covers training debugging, hyperparameter tuning, and production monitoring. Trigger keywords: model evaluation, metrics, accuracy, precision, recall, F1, F1-score, ROC, AUC, ROC-AUC, confusion matrix, cross-validation, k-fold, stratified, overfitting, underfitting, bias, variance, bias-variance tradeoff, hyperparameter, hyperparameter tuning, loss, loss function, met

针对中国A股的行情与数据查询（基于本地 akshare 源代码与API映射）。当用户请求获取A股实时行情、历史K线（日/周/月）、分钟级分时（1/5/15/30/60）、复权数据（前复权/后复权）、股东户数（含详情）、以及巨潮资讯公告披露结果时使用本Skill。默认优先使用东方财富(EM)接口；如用户指定新浪(Sina)来源或需要特定接口，则按映射调用对应函数。可使用内置脚本输出CSV/JSON，或内联Python调用。

Use the M4 Python API to query clinical datasets (MIMIC-IV, eICU) programmatically. Triggers on "M4 API", "query MIMIC with Python", "clinical data analysis", "EHR data", "execute SQL on MIMIC", or when writing code to access clinical databases.

Generate comprehensive implementation plan based on analysis. Use when user asks to plan this, create a plan, how should I implement, or wants implementation guidance.

This skill should be used when the user asks to "read NetCDF files", "work with xarray", "analyze climate data", "process satellite data", "use DataArray", "create Dataset", "work with multidimensional data", "use Dask with xarray", "read Zarr files", "work with labeled arrays", "use DataTree", "process raster data with rioxarray", or needs guidance on Xarray, NetCDF/HDF5/Zarr I/O, labeled multidimensional arrays, climate/satellite/oceanographic data analysis, Dask integration for large datasets

Comprehensive Wardley mapping toolkit that transforms any input (structured data, unstructured text, business descriptions, technical architectures, competitive landscapes, or abstract concepts) into strategic Wardley maps. Creates visual maps showing component evolution and value chains for strategic decision-making.

Executes tdx CLI commands for Treasure Data. Covers `tdx databases`, `tdx tables`, `tdx query`, `tdx auth setup`, context management with profiles/sessions, and output formats (JSON/TSV/table). Use when users need tdx command syntax, authentication setup, database/table exploration, or query execution.

Helps write Python code using the everyrow SDK for AI-powered data processing - transforming, deduping, merging, ranking, and screening dataframes with natural language instructions

This skill teaches how to use Miro MCP tools effectively for creating diagrams, documents, tables, and extracting context from Miro boards. Use when the user asks about Miro capabilities, wants to create content on Miro boards, or needs to work with Miro board data.

Create proper tables in Google Slides presentations using the Slides API. Use when building tabular data, metrics, comparisons, or any slide that needs rows and columns.

General-purpose agent for researching complex questions and executing multi-step tasks. Versatile problem-solver that combines research capabilities, analytical thinking, and systematic task execution. Use for complex research projects, multi-step workflows, cross-domain analysis, and tasks requiring multiple tools and approaches.

Expert in high-performance CSV processing, parsing, and data cleaning using Python, DuckDB, and command-line tools. Use when working with CSV files, cleaning data, transforming datasets, or processing large tabular data files.

Export Pixel Detective UMAP projections with HDBSCAN and manage Qdrant collections via the ingestion API. Use when the user asks for latent space exports, UMAP clustering assets, or collection operations (list/create/select/delete/merge).

Comprehensive skill for interacting with Grafana's HTTP API to manage dashboards, data sources, folders, alerting, annotations, users, teams, and organizations. Use when Claude needs to (1) Create, read, update, or delete Grafana dashboards, (2) Manage data sources and connections, (3) Configure alerting rules, contact points, and notification policies, (4) Work with folders and permissions, (5) Manage users, teams, and service accounts, (6) Create or query annotations, (7) Execute queries again

Matomo (Piwik) analytics platform API. Use for web analytics, tracking implementation, reporting API integration, plugin development, PHP/JavaScript tracking clients, and database schema understanding.

Expert data analyst specializing in business intelligence, data visualization, and statistical analysis. Masters SQL, Python, and BI tools to transform raw data into actionable insights with focus on stakeholder communication and business impact.

Expert trend analyst specializing in identifying emerging patterns, forecasting future developments, and strategic foresight. Masters trend detection, impact analysis, and scenario planning with focus on helping organizations anticipate and adapt to change.

Builds repeatable evaluation systems with golden datasets, scoring rubrics, pass/fail thresholds, and regression reports. Use for "LLM evaluation", "testing AI systems", "quality assurance", or "model benchmarking".

Generate structured decision-making tools — step-by-step guides, bias checkers, scenario explorers, and interactive dashboards. Use when facing significant choices requiring systematic analysis. Supports multiple cognitive styles and output formats.

Master interactive dashboard and application development with Panel and Param. Use this skill when building custom web applications with Python, creating reactive component-based UIs, handling file uploads and real-time data streaming, implementing multi-page applications, or developing enterprise dashboards with templates and theming.

Master quick plotting and interactive visualization with hvPlot. Use this skill when creating basic plots (line, scatter, bar, histogram, box), visualizing pandas DataFrames with minimal code, adding interactivity and hover tools, composing multiple plots in layouts, or generating publication-quality visualizations rapidly.

Analyze data files using lookup guides. Use when the user needs to interpret CSV data with code lookups, or process data files that require reference documentation.

Detect patterns, anomalies, and trends in code and data. Use when identifying code smells, finding security vulnerabilities, or discovering recurring patterns. Handles regex patterns, AST analysis, and statistical anomaly detection.

FAST code generation via mcp__cerebras-mcp__write tool using Z.ai glm-4.6. Use for rapid test generation, boilerplate creation, and bulk code tasks in main chat. Prompt must be SHORTER than output. Ideal for tests, CRUD, migrations, and repetitive patterns.

Use when estimating time, effort, or complexity for features or projects - provides structured estimation workflows with breakdowns, risks, and confidence intervals.

Compute text stats via text_stats tool.

dbt with TD Trino. Covers profiles.yml setup (method:none, user:TD_API_KEY), required override macros (no CREATE VIEW), TD_INTERVAL in models, and TD Workflow deployment.

Expert agent for debugging Keboola Python components using Keboola MCP tools, Datadog logs, and local testing. Specializes in identifying root causes of failures and providing actionable fixes.

Provide development estimates for tasks, features, or projects with intelligent analysis. Use when planning timelines, assessing complexity, or scoping resources.

Perform statistical hypothesis testing, regression analysis, ANOVA, and t-tests with plain-English interpretations and visualizations.

Use when asked to calculate statistical power, determine sample size, or plan experiments for hypothesis testing.

Debug and investigate code issues using search and AI analysis. Use when stuck on bugs, tracing execution flow, or understanding complex code.

Instructions for querying Google BigQuery using the bq command-line tool. Useful for running SQL queries, exploring datasets, and exporting results.

Expert assistant for choosing and implementing scientific workflow tools - from simple joblib caching to complex orchestration with Prefect, Parsl, FireWorks, and quacc. Recommends the simplest solution that meets requirements.

Automated hypothesis generation and testing using large language models. Use this skill when generating scientific hypotheses from datasets, combining literature insights with empirical data, testing hypotheses against observational data, or conducting systematic hypothesis exploration for research discovery in domains like deception detection, AI content detection, mental health analysis, or other empirical research tasks.

Comprehensive toolkit for creating, analyzing, and visualizing complex networks and graphs in Python. Use when working with network/graph data structures, analyzing relationships between entities, computing graph algorithms (shortest paths, centrality, clustering), detecting communities, generating synthetic networks, or visualizing network topologies. Applicable to social networks, biological networks, transportation systems, citation networks, and any domain involving pairwise relationships.

Expert for developing Streamlit data apps for Keboola deployment. Activates when building, modifying, or debugging Keboola data apps, Streamlit dashboards, adding filters, creating pages, or fixing data app issues. Validates data structures using Keboola MCP before writing code, tests implementations with Playwright browser automation, and follows SQL-first architecture patterns.