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Found 739 Skills
PreToolUse security-anti-pattern hook for Claude Code. Catches 12 common security risks (command injection, XSS, SQL injection, unsafe deserialization, GitHub Actions workflow injection, eval/new Function code injection) BEFORE the Edit/Write/MultiEdit operation completes. Session-state caching prevents duplicate warnings on the same file+rule combo. Stdlib only — no dependencies. Use when you want a safety net during Claude Code sessions that touch security-sensitive code (auth, payments, user input handling, IaC). Disable with ENABLE_SECURITY_REMINDER=0 if you need to perform a verified-safe operation that would otherwise trip a pattern. Triggers — "add security hook", "block unsafe code", "detect command injection before write", "prevent SQL injection patterns", "security warning hook".
Build ETL pipelines and analytics dashboards for Harvard Art Museums API data using Python, SQL, and Streamlit
End-to-end data engineering and analytics application using Harvard Art Museums API with ETL pipelines, SQL analytics, and Streamlit visualization
End-to-end ETL pipeline for Harvard Art Museums API with SQL analytics and Streamlit visualization
Build end-to-end ETL pipelines with Harvard Art Museums API, SQL analytics, and Streamlit visualization
End-to-end retail ETL pipeline using PySpark, SQL Server, and Medallion Architecture (Bronze/Silver/Gold layers) for data warehousing
SQLiteData queries, @Table models, Point-Free SQLite, RETURNING clause, FTS5 full-text search, CloudKit sync, CTEs, JSON aggregation, @DatabaseFunction
Creates dbt models following project conventions. Use when working with dbt models for: (1) Creating new models (any layer - discovers project's naming conventions first) (2) Task mentions "create", "build", "add", "write", "new", or "implement" with model, table, or SQL (3) Modifying existing model logic, columns, joins, or transformations (4) Implementing a model from schema.yml specs or expected output requirements Discovers project conventions before writing. Runs dbt build (not just compile) to verify.
Optimizes Snowflake SQL query performance from provided query text. Use when optimizing Snowflake SQL for: (1) User provides or pastes a SQL query and asks to optimize, tune, or improve it (2) Task mentions "slow query", "make faster", "improve performance", "optimize SQL", or "query tuning" (3) Reviewing SQL for performance anti-patterns (function on filter column, implicit joins, etc.) (4) User asks why a query is slow or how to speed it up
Web vulnerability testing patterns for SQL injection, XSS, CSRF, LFI, SSTI, and file upload bypasses in CTF challenges. Trigger: When testing web applications, SQL injection, XSS, or file uploads.
Database design, SQL, NoSQL, and data management patterns
Create Databricks AI/BI dashboards. CRITICAL: You MUST test ALL SQL queries via execute_sql BEFORE deploying. Follow guidelines strictly.