Data & Analytics

josiahsiegel Bundle

Microsoft Fabric integration with Power BI semantic models. PROACTIVELY activate for: (1) Microsoft Fabric platform tasks, (2) Direct Lake mode and OneLake connectivity, (3) Fabric lakehouse, warehouse, KQL Database, Eventstream, Data Activator, (4) Dataflow Gen2 ETL, (5) Fabric notebooks (PySpark, Spark SQL, semantic-link), (6) Fabric workspace and capacity (F-SKU) management, (7) delta tables and V-Order optimization, (8) medallion architecture (bronze/silver/gold), (9) Semantic Link / sempy / semantic-link-labs Python workflows, (10) Direct Lake fallback rules and mixed mode. Provides: Direct Lake setup, Fabric capacity sizing, lakehouse-to-semantic-model patterns, sempy/semantic-link-labs recipes, and end-to-end medallion architecture templates.

josiahsiegel Skill

Kaggle competition notebook workflows and submissions. PROACTIVELY activate for: (1) submitting notebook outputs to competitions, (2) `kaggle competitions submit -k`, (3) downloading competition data, (4) validating submission.csv format, (5) leakage review, (6) cross-validation split design, (7) public leaderboard overfitting concerns, (8) competition rule compliance, (9) reproducible top-to-bottom notebook execution, (10) fold-aware preprocessing for ML pipelines. Provides: submission commands, validation checklist, leakage controls, and competition-ready notebook guidance.

josiahsiegel Bundle

This skill should be used when the user asks to analyze SQL Server execution plans, .sqlplan files, ShowPlan XML, actual vs estimated plans, plan warnings, or operator costs. PROACTIVELY activate for: .sqlplan triage, ShowPlan XML inspection, high-cost operator ranking, scan vs seek review, residual predicate analysis, CONVERT_IMPLICIT warnings, bad row estimates, cardinality-estimation warnings, partition elimination verification, missing-index suggestions, unused-index warnings, spills, key lookups, sorts, hash joins, and plan-regression evidence gathering. Provides: plan triage workflow, operator-cost ranking heuristics, warning interpretation rubric, and rewrite/index recommendation gating.

josiahsiegel Bundle

Cloudflare platform knowledge — Workers, Pages, R2, D1, KV, Durable Objects, AI, and Zero Trust. PROACTIVELY activate for: (1) Cloudflare Workers (handlers, bindings, wrangler), (2) Cloudflare Pages and Pages Functions, (3) R2 object storage, (4) D1 SQL database, (5) Workers KV and Durable Objects, (6) Workers AI inference (LLMs, embeddings, image gen), (7) Vectorize (vector database), (8) Queues and Email Workers, (9) Zero Trust (Access, Tunnel/cloudflared, Gateway), (10) DNS, WAF, Rate Limiting, Page Rules. Provides: wrangler.toml templates, binding patterns, R2/D1/KV usage, Workers AI examples, and Zero Trust config.

josiahsiegel Skill

credit_transactions audit trail invariants and daily reconciliation patterns. PROACTIVELY activate for: (1) Designing a credit / balance / entitlement ledger, (2) credit_transactions row shape (delta, balanceAfter, reason, referenceType, referenceId, idempotencyKey), (3) Canonical idempotency key formats (refund:/debit:/stripe_checkout:/stripe_invoice:/stripe_refund:/stripe_signup_bonus:/dispute_hold:/dispute_restore:), (4) Daily reconciliation cron design (snapshot comparison, not full-sum), (5) Alert-only policy (never auto-correct drift), (6) Canonical refund helper pattern (single source of truth across pg-raw and Drizzle call sites), (7) Past_due block + credit balance shared preflight, (8) creditsDeducted boolean return pattern for pre- vs post-deduction error differentiation, (9) Money-safe email description based on resolvedVia flag, (10) Skip-users-without-baseline-snapshot reconciliation logic. Provides: table schema, canonical helper skeleton, reconciliation SQL, email gating pattern.

josiahsiegel Skill

Server-side Stripe webhook idempotency patterns. PROACTIVELY activate for: (1) Stripe webhook handler design, (2) Transactional dedup via stripe_processed_events, (3) credit_transactions.idempotency_key UNIQUE partial indexes, (4) Idempotency-Key header priority (header > body > server UUID), (5) Idempotency key format/charset/length validation at the handler edge, (6) FOR UPDATE row locking when a UPDATE depends on a prior SELECT, (7) Webhook signature verification (stripe.webhooks.constructEventAsync, tolerance, raw-body reading), (8) Retry-safe endpoints with randomUUID fallback, (9) Durable checkpoint row ordering (checkpoint FIRST, mutation SECOND). Provides: complete webhook handler skeleton, Idempotency-Key validator, dedup SQL, FOR UPDATE pattern, signature verification example.

practicalswan Bundle

Use this skill any time a spreadsheet file is the primary input or output. Covers reading, editing, cleaning, modeling, formula repair, workbook generation, and converting tabular data into validated spreadsheet deliverables.

practicalswan Bundle

Excel (.xlsx) manipulation via MCP server. Use for creating workbooks, formatting cells, writing formulas, building charts, pivot tables, data analysis, or any task involving Excel spreadsheets.

practicalswan Bundle

NVIDIA DeepStream SDK development guidance for Python pyservicemaker pipelines, video analytics, TensorRT integration, and streaming inference workflows.

practicalswan Bundle

T-SQL, stored procedures, and MS SQL Server DBA practices. Use when writing SQL queries, designing schemas, tuning SQL Server performance, managing backups, configuring security, or using SQL Server 2025+ features.

practicalswan Bundle

Inspect CSV datasets for schema, quality, modeling readiness, and feature analysis.

practicalswan Bundle

Use this skill for Hugging Face Dataset Viewer API workflows that fetch subset/split metadata, paginate rows, search text, apply filters, download parquet URLs, and read size or statistics.

practicalswan Bundle

MongoDB schema design patterns and anti-patterns. Use when designing data models, reviewing schemas, migrating from SQL, or troubleshooting performance issues caused by schema problems. Triggers on "design schema", "embed vs reference", "MongoDB data model", "schema review", "unbounded arrays", "one-to-many", "tree structure", "16MB limit", "schema validation", "JSON Schema", "time series", "schema migration", "polymorphic", "TTL", "data lifecycle", "archive", "index explosion", "unnecessary indexes", "approximation pattern", "document versioning".

practicalswan Bundle

Analyze git repositories to build a security ownership topology (people-to-file), compute bus factor and sensitive-code ownership, and export CSV/JSON for graph databases and visualization. Trigger only when the user explicitly wants a security-oriented ownership or bus-factor analysis grounded in git history (for example: orphaned sensitive code, security maintainers, CODEOWNERS reality checks for risk, sensitive hotspots, or ownership clusters). Do not trigger for general maintainer lists or non-security ownership questions.

practicalswan Bundle

Inspect PDFs, DOCX, PPTX, and XLSX files for share-readiness, metadata, links, comments, and hidden content.

practicalswan Bundle

Official NVIDIA-authored guidance for NVIDIA cuDF GPU DataFrames, pandas acceleration, dask-cuDF, ETL, joins, groupby, CSV/Parquet I/O, nullable semantics, and multi-GPU DataFrame workloads.

practicalswan Bundle

Write and debug spreadsheet formulas (Excel/Google Sheets), pivot tables, and array formulas; translate between dialects; use when users need working formulas with examples and edge-case checks.

practicalswan Bundle

Postgres best practices maintained by Supabase, for Postgres running anywhere. Load this skill BEFORE writing or changing anything that lives in a Postgres database: creating or altering tables and columns (including choosing column types), schema design, migrations and declarative schema files, RLS policies and the tests that verify them, indexes, triggers, database functions, queues and scheduled jobs (pg_cron, pgmq), vector/semantic search (pgvector), and restoring dumps (pg_restore) or importing data. Also load it when diagnosing slow queries, high CPU, timeouts, EXPLAIN plans, connection exhaustion, locking, bloat, or rows visible to the wrong user or tenant. This is not just a performance guide — schema, migration, security, and SQL authoring tasks need these rules too, even for a one-column change or a single query.

practicalswan Bundle

Generate read-only MongoDB queries (find) or aggregation pipelines using natural language, with collection schema context and sample documents. Use this skill whenever the user asks to write, create, or generate MongoDB queries, wants to filter/query/aggregate data in MongoDB, asks "how do I query...", needs help with query syntax, or discusses finding/filtering/grouping MongoDB documents. Also use for translating SQL-like requests to MongoDB syntax. Does NOT handle Atlas Search ($search operator), vector/semantic search ($vectorSearch operator), fuzzy matching, autocomplete indexes, or relevance scoring - use search-and-ai for those. Does NOT analyze or optimize existing queries - use mongodb-query-optimizer for that. Does NOT handle aggregation pipelines that involve write operations. Requires MongoDB MCP server.

aj-geddes-useful-ai-prompts Bundle

Identify security vulnerabilities through SAST, DAST, penetration testing, and dependency scanning. Use for security test, vulnerability scanning, OWASP, SQL injection, XSS, CSRF, and penetration testing.

aj-geddes-useful-ai-prompts Bundle

Analyze and optimize SQL queries for performance. Use when improving slow queries, reducing execution time, or analyzing query performance in PostgreSQL and MySQL.

aj-geddes-useful-ai-prompts Bundle

Integrate external APIs and services with error handling, retry logic, and data transformation. Use when connecting to payment processors, messaging services, analytics platforms, or other third-party providers.

aj-geddes-useful-ai-prompts Bundle

Prevent SQL injection attacks using prepared statements, parameterized queries, and input validation. Use when building database-driven applications securely.

mindrally Skill

Best practices for building performant, testable PySpark ETL pipelines with Spark SQL and Apache Iceberg. Use when writing or reviewing PySpark jobs, designing joins and window functions, working with map/array higher-order functions, or building idempotent cumulative/snapshot table merges.

mindrally Skill

SQL development best practices for writing efficient, secure, and maintainable database queries

mindrally Skill

Reference for Snowflake Cortex AI Functions (AI_COMPLETE, AI_CLASSIFY, AI_EXTRACT, AI_FILTER, etc.) and Cortex Search for building RAG applications entirely inside Snowflake. Use when writing SQL that calls an LLM, classifying or extracting structured data from text, building a natural-language WHERE filter, or setting up hybrid vector+keyword search for retrieval-augmented generation.

mindrally Skill

Best practices for Pandas data manipulation, analysis, and DataFrame operations in Python

mindrally Skill

Best practices for Snowflake SQL, semi-structured data, and data pipelines built with Dynamic Tables, Streams, Tasks, and Snowpipe. Use when writing Snowflake SQL, designing ingestion or transformation pipelines, tuning warehouse performance and cost, or working with Time Travel, cloning, RBAC, or Iceberg tables on Snowflake.

rmyndharis Skill

Expert data scientist for advanced analytics, machine learning, and statistical modeling. Handles complex data analysis, predictive modeling, and business intelligence. Use PROACTIVELY for data analysis tasks, ML modeling, statistical analysis, and data-driven insights.

rmyndharis Skill

Master modern business analysis with AI-powered analytics, real-time dashboards, and data-driven insights. Build comprehensive KPI frameworks, predictive models, and strategic recommendations. Use PROACTIVELY for business intelligence or strategic analysis.

rmyndharis Skill

Transform data into compelling narratives using visualization, context, and persuasive structure. Use when presenting analytics to stakeholders, creating data reports, or building executive presentations.

aliyun Bundle

Alibaba Cloud RDS Copilot intelligent operations assistant skill. Used for RDS-related intelligent Q&A, SQL optimization, instance operations, and troubleshooting. Calls RdsAi OpenAPI through Alibaba Cloud CLI to get real-time RDS Copilot responses. Triggers: "RDS Copilot", "RDS Assistant", "SQL optimization", "RDS troubleshooting", "RDS operations", "database diagnosis"

aliyun Bundle

Design partition schemes, select partition keys, create GSI, and write SQL for PolarDB-X 2.0 Enterprise Edition AUTO mode databases, handling PolarDB-X vs MySQL differences (partitioned tables, GSI, CCI, Sequence, table groups, TTL, pagination, etc.). Use when designing partition schemes, selecting partition keys, converting single tables to partitioned tables, creating GSI/CCI indexes, writing or migrating SQL for PolarDB-X, or diagnosing slow queries on PolarDB-X. Triggers: "PolarDB-X SQL", "PolarDB-X create table", "partitioned table", "partition design", "partition scheme", "partition key", "GSI", "CCI", "Sequence", "MySQL migrate to PolarDB-X", "PolarDB-X compatibility", "single table to partitioned table", "convert to partitioned table", "large table", "table sharding", "distributed table", "AUTO mode", "pagination query", "Keyset pagination", "Range partition", "auto add partition", "PolarDB-X slow query", "full-shard scan"

aliyun Bundle

Query and manage Alibaba Cloud RDS instances in the user's own account through Alibaba Cloud CLI and official RDS, VPC, BssOpenApi, and DAS OpenAPIs. Use for listing or inspecting RDS instances, zones, classes, performance, logs, parameters, databases, accounts, networks, whitelists, bills, and SQL insight statistics, or for explicitly requested instance creation, parameter/specification/description changes, account creation, whitelist changes, public endpoint allocation, whitelist-template attachment, tagging, restart, and instance deletion. Do not use this skill to diagnose incidents, troubleshoot performance anomalies, or perform root-cause analysis; it only queries current RDS instance state and executes the explicitly supported instance-management operations.

aliyun Bundle

跨大数据引擎的 SQL 语法转换技能（DML/DDL/存储过程）。覆盖标识符、数据类型、函数、查询语法、分布/分区策略、存储过程/函数、外表等重写场景。目前已实现 Synapse → Hologres，框架为其他引擎对（如 SQL Server → MaxCompute、Hive → Hologres、PostgreSQL → Hologres、Oracle → MaxCompute 等）预留了可扩展位置（TODO）。当用户需要将 SQL/T-SQL/PL-SQL 从一个数仓转换到另一个数仓、跨源迁移查询语句、T-SQL 转 PostgreSQL、数仓 SQL 兼容性改写时使用。不适用于：表结构 DDL 迁移（用 ddl-trans）、ADF 工作流迁移（用 adf2dw）、数据集成作业生成（用 dw-di-generator）。已知局限：不支持递归 CTE、动态 SQL 拼接、SQL Server GEOGRAPHY/GEOMETRY 等空间类型；基于规则匹配，转换结果建议人工审核。

aliyun Bundle

Quick BI-SmartQ skill with multiple data analysis capabilities: 1. **File Q&A**: Upload Excel/CSV files for intelligent analysis via Quick BI API 2. **Dataset Q&A**: Natural language queries on Quick BI platform datasets, with automatic intelligent table selection and matching 3. **Document Parsing**: Parse PDF/Word/Excel/CSV/images, extract text, and support extracting key fields to generate structured Excel 4. **Dashboard Skill Generation**: Auto-convert QuickBI dashboards into data query skills 5. **Data Insight**: Deep data insight analysis on Quick BI datasets 6. **Data Report**: Auto-generate professional data reports based on analysis results Use when users mention data analysis, smart Q&A, querying data, file analysis, document parsing, dashboard skills, data insight, or data reports.