Data & Analytics

skillmedev Skill

Runs a structured exploratory data analysis on a new or suspect dataset - schema audit, target analysis, feature profiling, missingness patterns, and leakage checks - ending in a written decision log. Use when someone says "I just got this dataset, where do I start", "my model metrics look too good", "audit this data before we model it", or is debugging unexpected model behavior. Do NOT use for writing the transformation code itself - use pandas-expert instead; for ongoing production data monitoring use data-quality; for constructing model features after EDA use ml-feature-engineering; for answering a one-off business question from a database use sql-to-insights.

skillmedev Skill

Designs normalized, constrained, migration-friendly relational schemas - entity modeling, key and type selection, indexes derived from real query patterns, and safe forward/rollback migrations. Use when someone asks "design a schema for X", "should I normalize or denormalize this", "what should my primary key be", "how do I add this column without downtime", or "why is my unique constraint broken with soft deletes". Do NOT use for tuning a slow query on an existing schema - use sql-query-optimizer instead; for picking indexes from a live workload, use index-advisor; for sizing database connection pools, use connection-pool-tuner; for range/hash partitioning decisions, use partition-planner.

skillmedev Skill

Builds secure Supabase apps - Row Level Security policies as the authorization layer, schema design against auth.users, Edge Functions for service-role work, realtime subscriptions, and versioned migrations. Use when someone asks "set up RLS for my tables", "is my Supabase app secure", "anyone can read my table with the anon key", "when do I need an Edge Function", or "why is my realtime subscription not receiving rows". Do NOT use for general Postgres schema design without Supabase - use database-schema instead; for tuning slow queries, use sql-query-optimizer; for Stripe billing inside a Supabase app, use stripe-integration.

skillmedev Skill

Product Analytics

azlekov Bundle

This skill should be used when the user asks to "integrate Stripe", "add payments", "create subscriptions", "handle webhooks", "usage-based billing", "per-seat pricing", "tiered plans", "checkout session", "customer portal", "sync Stripe data", "Stripe Sync Engine", "payment processing", "MRR analytics", "revenue reporting", or mentions 'Stripe', 'subscription', 'billing', 'webhook', 'checkout', 'metered billing', 'payment intent', 'stripe schema'. Automatically triggers for payment, subscription, and billing analytics work.

wilsonfreitas Skill

Connect to BrasaDB's DuckDB database and execute SQL queries to explore Brazilian financial market data. Use this skill whenever the user asks to query, explore, analyze, or study data in the brasa database, asks about available datasets or tables, wants to run SQL queries against financial data, wants to create views or combine datasets for a specific application, or mentions DuckDB, BrasaDB, or SQL in the context of this project. Also trigger when the user asks questions that could be answered by querying the data — e.g., "what stocks are in IBOV?", "show me PETR4 prices", "what's the DI1 curve?", "help me create a view with these datasets", "I have datasets A and B, combine them for X".

maxbase91 Bundle

Analyse procurement spend data from Coupa, Ariba, SAP, Concur, Oracle, or generic CSV/XLSX exports. Use whenever the user shares spend data and asks for categorisation, supplier consolidation, anomaly detection, savings opportunities, tail spend analysis, maverick spend, or category breakdowns. Trigger on phrases like "analyse this spend", "categorise these suppliers", "find anomalies in my spend", "where's my tail spend", "Coupa export", "Ariba data", "spend cube", "supplier consolidation opportunities", or whenever a procurement-flavoured spreadsheet of transactions is shared. Produces a structured spend brief with category breakdown, top suppliers, anomalies, and actionable savings opportunities.

ocean1346 Bundle

Use when writing, reviewing, or optimizing BigQuery SQL, asking about BigQuery best practices, working with .sql files targeting BigQuery, or troubleshooting slow/expensive BigQuery queries. Symptoms: high slot consumption, full table scans, expensive joins, slow queries, high bytes billed.

ocean1346 Bundle

Use when generating BigQuery SQL from natural language descriptions, converting queries from other SQL dialects to BigQuery, writing new BigQuery queries from scratch, or when the user describes what data they need and expects SQL output. Triggers on: "write me a query", "generate SQL", "how do I query", "convert this to BigQuery", "I need to get data from", "create a query".

beau-education Skill

Generate business-intelligence reports on how students and teachers use the Beau platform — engagement, content authoring, and commerce — from the org-scoped analytics event log via MCP. For org admins. Produces periodic, evidence-based usage summaries.

full-stack-skills Bundle

Provides comprehensive guidance for MySQL including SQL syntax, functions, indexing, optimization, replication, backup, and high availability. Use when the user asks about MySQL, needs to write MySQL queries, design database schemas, optimize performance, or manage MySQL databases.

full-stack-skills Bundle

Provides comprehensive guidance for Oracle database including SQL, PL/SQL, functions, performance tuning (AWR/ASH), backup (RMAN), Data Guard, and RAC. Use when the user asks about Oracle, needs to write Oracle SQL, work with PL/SQL, or manage Oracle databases.

full-stack-skills Bundle

Provides comprehensive guidance for PostgreSQL including SQL syntax, advanced features (JSONB/CTE/Full-text), functions, indexing, performance tuning, replication, and backup. Use when the user asks about PostgreSQL, needs to work with PostgreSQL features, write complex queries, or optimize PostgreSQL databases.

cprima-agents Bundle

Convert mixed-format files in one or more source folders into markdown-ready output for reading, analysis, or elicitation. Produces a sibling <foldername>_harvested/ folder containing manifest.json, inventory.md, and converted files organised by type. Converts .msg, .docx, .pdf, .xlsx/.xls by extension; copies images as-is. Use when the user points at a folder of source files and wants them prepared for later analysis — e.g. "harvest this testdata folder", "convert these docs for reading", "prepare these mails for analysis", or "I have a folder of mixed files, read them".

cprima-agents Bundle

Generate a typed C# CodedConfig class and a UiPath clipboard snippet from a REFramework Config.xlsx. Use when a developer wants to replace dictionary-based settings lookups with strongly-typed C# properties in a UiPath REFramework project. Triggers on: typed config, CodedConfig, ConFormMold, Config.xlsx to class, typed settings, REFramework config, InitAllSettings typed, strongly-typed config.

cyanluna-git Bundle

CSV Worklog Migration Skill

databricks-solutions Skill

Execute code on Databricks clusters using MCP Command Execution API. Supports stateless quick validation and stateful iterative development. Use when testing Python/SQL code on clusters, debugging pipelines, or validating transformations.

databricks-solutions Skill

Production data engineering pipelines following medallion architecture (Bronze/Silver/Gold layers) with data ingestion, transformation, quality checks, Delta Lake optimization, and orchestration. Use when building ETL pipelines, medallion architecture, data lakes, or data transformation workflows.

databrickslabs Skill

Create DQX quality rules (checks) for a PySpark DataFrame or Delta table. Use when the user asks to "add a DQX check", "define a data quality rule", "validate that column X is not null / unique / in a set", or wants checks expressed in YAML/JSON for storage. Covers DQRowRule, DQDatasetRule, DQForEachColRule, built-in check_funcs, filters, user_metadata, custom SQL/Python checks, and the declarative metadata form.

databrickslabs Skill

Profile a DataFrame or table and generate DQX quality rule candidates with summary statistics. Use when the user asks to "profile a table", "generate DQX rules from data", "suggest data quality checks", "bootstrap a checks.yml", or "generate DLT expectations". Covers DQProfiler, DQGenerator, DQDltGenerator, the profiler workflow, sampling / filter options, and AI-assisted variants.

datadata-team Bundle

本技能包含了 Datadata DQL 查询脚本语言的完整参考文档，当使用 Datadata DQL 脚本时，**必须先加载本技能**。 Write DQL data processing scripts for the Datadata platform — a Starlark-based extended scripting language supporting DataFrame/Series operations, SQL queries, HTTP requests, and more. Use when the user needs to write data transformation, data cleaning, data generation, or custom data processing logic.

datadata-team Bundle

本技能包含对 Datadata 平台的详细操作手册，在使用 Datadata 平台相关功能时，**必须先加载本技能**。 Datadata 平台功能包括: 1. 数据源管理 - 搜索、查询、元数据增强 2. 执行 Query 查询 - 对数据源执行 SQL、DQL 查询，并获取结果 3. Data Spaces 数据空间管理 - 创建数据空间、通过 SQL 管理表结构与数据

datadata-team Bundle

本技能包含了 Datadata Python 查询脚本的完整参考文档，当编写 Datadata Python 查询脚本时，**必须先加载本技能**。 Write Python data query scripts for the Datadata platform — real Python (RustPython/WASM sandbox) with a Polars-style DataFrame/Series/Expr API, SQL data access via query(), and HTTP requests via fetch(). Use when the user needs to write data transformation, data cleaning, data generation, or custom data processing logic in Python.

datadata-team Bundle

本技能提供对 Datadata 平台 Rest API 的完整参考文档，在使用 Datadata Rest API 之前，**必须先加载本技能**。 本技能提供完整的 API 端点说明和 urllib.request（零额外依赖）调用示例。 首要用例是生成爬虫、ETL、批处理脚本，同时适用于所有需要直接调用 Datadata API 的场景。 涵盖数据源查询、SQL 执行、结果下载、Dataspace SQL 执行全流程。 使用场景： 1. 生成独立 Python 脚本（爬虫、ETL、批处理） 2. 生成定时任务脚本，比如每天定时爬去最新金融数据，并写入 Data Space 数据空间。

wazuh Skill

Resolve a dependency CVE in the Wazuh Dashboard alerting plugin — confirm the vulnerable package is actually present and reachable, apply the least-invasive remediation (direct bump, lockfile dedupe, or scoped resolution), verify build/tests/audit, and hand off a prepared PR. Use when the user asks to fix or resolve a CVE / dependency vulnerability, or provides a CVE id or CVE issue URL.

jame581 Skill

Lint and repair the Claude Brain Logseq graph — find and fix format violations that create phantom pages or broken macros. Triggers: "brain doctor", "lint brain", "check brain health", "clean up brain", "fix brain", "graph hygiene", "why are there empty pages", "find broken pages", "backfill digests", "rebuild digest for <project>". Don't fire for loads (use brain-load), saves (use brain-save), status/analytics (use brain-status), or first-time setup (use brain-init).

jame581 Skill

Show a dashboard of all projects in the Claude Brain graph, or graph analytics. Dashboard triggers: "brain status", "show projects", "show brain", "what's in my brain", "project dashboard", "brain overview", "list projects", "summary". Analytics triggers: "brain stats", "graph analytics", "graph activity over time". Don't fire for loads (use brain-load) or saves (use brain-save).

jbaham2 Bundle

Monitors and analyzes LLM application data already in Langfuse — dashboards, metrics, and alerting for cost, latency, quality, and volume. Use whenever the user wants to observe or report on production Langfuse data: "monitor my LLM app", "build a Langfuse dashboard", "track cost / latency / quality over time", "Langfuse metrics API", "score analytics", "set up a spend alert", "alert me when costs spike", "dashboard for production monitoring", or interpreting usage/cost/quality trends. Owns operating-the-data (dashboards/metrics/alerting); defers instrumentation to the vendored `langfuse` skill and score/evaluator design to the `langfuse-evaluation` skill.

jleonceo Skill

Skill de exploración del enjambre de audiencias. Se activa cuando hay datos (GA4, Search Console, redes, email, CSV exportados). Análisis estructurado: estructura, calidad, métricas clave, patrones temporales, segmentos y anomalías. Siempre antes de proyectar.

guygrigsby Skill

Use when writing or reviewing SQL DDL — creating a table, adding a column, designing a schema or a migration — before the first CREATE TABLE is typed. Also when a schema shows nullable status columns (returned_at, deleted_at, closed_at), foreign keys without ON DELETE, TEXT timestamps, application-generated surrogate ids, CHECK (col IN (...)) vocabularies, delimited lists or JSON columns standing in for child tables, or tables whose only key is the surrogate id.

hectorai-live Skill

Use this skill ANY TIME the user asks about keyword harvesting, finding keywords to add, identifying search terms not in exact match, or gap analysis — e.g. "harvest keywords", "what keywords should I add?", "which search terms should I be targeting in exact match?", "find terms with orders not in my exact targeting", "run a harvest for [brand/account]", "show me harvesting opportunities", "keyword gap analysis", or close paraphrases. Also fires when the user wants to add the harvested terms to existing or new campaigns (action phase). Does NOT fire for: "show me my top search terms" (performance report only), "which search terms are wasting spend" (negative keyword task), "what keywords should I pause/remove" (bid or status task), general search-term analytics with no intent to promote terms, placement analysis, or budget questions.

lalitmaganti Skill

Debug a SQL formatter bug. Use when the user reports incorrect formatting, such as wrong whitespace, misplaced comments, or blank lines.

lalitmaganti Skill

Parse SQL and inspect the AST using syntaqlite. Use when the user wants to see the parse tree, debug SQL syntax, or understand how a query is structured.

lalitmaganti Skill

Format SQL files using the syntaqlite formatter. Use when the user wants to format, reformat, or pretty-print SQL code.

lalitmaganti Skill

Validate SQL and report diagnostics using syntaqlite. Use when the user wants to check SQL for errors, lint SQL files, or verify correctness against a schema.

lineofflight Skill

Manages Cloudflare zones via API. Use when purging cache, querying DNS records, or checking zone analytics.