Skills for “sql”

Run LLM functions inside Spark SQL on AIDP via ai_generate(). Use when the user wants to summarize/classify/extract/enrich rows with an LLM directly in SQL, generate narratives over aggregated results, or do grounded…

Write-side Spark SQL on the AIDP lakehouse — DDL (CREATE/ALTER/DROP table·view·schema), DML (INSERT/UPDATE/DELETE/MERGE upsert), and Delta maintenance (OPTIMIZE, VACUUM, time travel, RESTORE, schema evolution, liquid…

No description in the SKILL.md.

Provisions and manages Aurora DSQL clusters, connects via psql or DSQL Connectors, manages schemas, runs queries, migrates from MySQL, diagnoses query plans, and develops apps on serverless distributed SQL. Covers IAM…

Register and validate reusable question→Spark-SQL pairs in .aidp/verified-queries.md so the agent reuses trusted SQL before generating new SQL. Use when the user wants to save a working query as canonical, build a…

…business questions over the AIDP lakehouse with Spark SQL. Use when the user asks a data question ("how many…", "top N…", "show me…", "trend of…", "revenue by…") or wants to run ad-hoc Spark SQL. Grounds in…

Execute and manage Athena SQL queries across default and federated catalogs (Glue, S3 Tables, Redshift). Triggers on phrases like: query data, run SQL, athena query, analyze table, SQL query, workgroup status, profile…

Amazon Redshift is NOT PostgreSQL; corrects LLM mistakes; covers SQL, metadata, connectivity/auth, storage, query performance, and operations. Applies ONLY to Redshift (provisioned or Serverless). Pushes back on: CREATE…

…layer (.aidp/semantic.md) for AIDP — logical entity names, SQL-defined metrics, joins with cardinality, synonyms, and value dictionaries. Use when the user wants to define metrics/business terms, improve NL-to-SQL…

…migration to Amazon Redshift — discovery, schema/SQL/stored-procedure/macro/script conversion, data migration, validation, performance comparison, and reporting. Source-routed via `references/<source>/`;…

…refresh catalog metadata, or test a connection. For SQL-native CREATE/ALTER/DROP use aidp-sql-ddl; for file→table ingestion use aidp-ingest-file-to-table; for browsing use…

Runs SQL analytics on SageMaker Catalog asset metadata tables exported as Apache Iceberg in S3 Tables. Covers governance queries, asset growth tracking, ownership audits, time-travel over catalog state, and metadata…

…a dataset's shape before using it. Runs bounded Spark SQL via the bundled aidp_sql.py…

…build an interactive notebook (e.g. with widgets + Spark SQL + Plotly). Notebook FILE ops run via the Notebook contents REST API; CELL EXECUTION runs via…

…and a trivial SELECT 1 cell via $HOME/.aidp/aidp_sql.py). Use on first run, when the user asks to "set up / configure / install / bootstrap AIDP", or when control-plane or SQL calls fail with auth/config…

…pipeline on quality. Expresses each rule as bounded Spark SQL and reports pass/fail with offending…

…need stage/task timings, skew, shuffle/spill, executor, or SQL-execution details. Lightweight triage — for deep performance tuning (skew/spill/shuffle/joins/AQE/Delta) use the `aidp-spark-optimization`…

Create and manage standalone reusable AIDP agent Tools — SQL, Prompt, RAG, HTTP, Custom, and MCP tools that can be shared across agent flows by key. Use when the user wants to define a reusable tool (not inline in one…

…schema changes to a target database, and converting SQL statements between database engines. Applies when migrating database schemas between heterogeneous engines using AWS DMS Schema…

…data estate, plan a migration to AIDP, translate Athena SQL or Glue ETL/PySpark to Spark on AIDP, or verify a migration's output. Wraps the `aws-aidp` CLI, with the verbs inventory, plan, migrate and…