📊 Data & Databases AI Skills

Use the @steipete/oracle CLI to bundle a prompt plus the right files and get a second-model review (API or browser) for debugging, refactors, design checks, or cross-validation.

Manage Things 3 via the `things` CLI on macOS (add/update projects+todos via URL scheme; read/search/list from the local Things database). Use when a user asks Clawdbot to add a task to Things, list inbox/today/upcoming, search tasks, or inspect projects/areas/tags.

Local search/indexing CLI (BM25 + vectors + rerank) with MCP mode.

Use when designing database schemas, writing migrations, optimizing SQL queries, fixing N+1 problems, creating indexes, setting up PostgreSQL, configuring EF Core, implementing caching, partitioning tables, or any database performance question.

Connect to Supabase for database operations, vector search, and storage. Use for storing data, running SQL queries, similarity search with pgvector, and managing tables. Triggers on requests involving databases, vector stores, embeddings, or Supabase specifically.

Query, design, migrate, and optimize SQL databases. Use when working with SQLite, PostgreSQL, or MySQL — schema design, writing queries, creating migrations, indexing, backup/restore, and debugging slow queries. No ORMs required.

Design data models for construction projects. Create entity-relationship diagrams, define schemas, and generate database structures.

Use SQLite correctly with proper concurrency, pragmas, and type handling.

Turn raw data into decisions with statistical rigor, proper methodology, and awareness of analytical pitfalls.

This skill should be used when the user asks to "design REST APIs", "optimize database queries", "implement authentication", "build microservices", "review backend code", "set up GraphQL", "handle database migrations", or "load test APIs". Use for Node.js/Express/Fastify development, PostgreSQL optimization, API security, and backend architecture patterns.

Query project databases with automatic SSH tunnel management. Use when you need to execute SQL queries against configured databases, especially those accessible only via SSH tunnels. Automatically manages SSH connection lifecycle (establishes tunnel before query, closes after). Supports multiple databases distinguished by description/name from config file.

Professional data visualization using Python (matplotlib, seaborn, plotly). Create publication-quality static charts, statistical visualizations, and interac...

Airtable API integration with managed OAuth. Manage bases, tables, and records. Use this skill when users want to read, create, update, or delete Airtable records, or query data with filter formulas. For other third party apps, use the api-gateway skill (https://clawhub.ai/byungkyu/api-gateway).

Use when optimizing SQL queries, designing database schemas, or tuning database performance. Invoke for complex queries, window functions, CTEs, indexing strategies, query plan analysis.

Write efficient PostgreSQL queries and design schemas with proper indexing and patterns.

Use Redis effectively for caching, queues, and data structures with proper expiration and persistence.

Local search/indexing CLI (BM25 + vectors + rerank) with MCP mode.

Knowledge graph operations via Graphiti API. Search facts, add episodes, and extract entities/relationships.

Track parcels via the 17TRACK API (local SQLite DB, polling + optional webhook ingestion)

Design schemas, write queries, and configure MongoDB for consistency and performance.

Design and operate databases avoiding common scaling, reliability, and data integrity traps.

Write Oracle SQL and PL/SQL with proper syntax, hints, and performance patterns.

Your data has answers. CellCog asks the right questions. #1 on DeepResearch Bench (Feb 2026) + frontier coding agent — upload messy CSVs with minimal prompting and get structured insights back: charts, dashboards, statistical reports, and clean data. Full Python access for data cleaning, exploratory analysis, visualization, hypothesis testing, ML model evaluation, and dataset profiling. Analyzes everything, presents it beautifully.

Local-first RAG cache: distill docs into structured Markdown, then index/query with Chroma (vector) + ripgrep (keyword).