check-data-flow

Use this Oracle Analytics domain skill when creating or editing Oracle Analytics Cloud workbooks, visualizations, calculations, filters, layouts, governed analyses, or when routing an analytics request to a more specific nested skill.

Parse and summarize the JOB_REPORT.md produced by a prior migration run. Surfaces cell pass/fail/fix counts per task, lists the failing cells, and recommends a next-step skill (fixup-cell, resume, or all-clear). Use after any aidp-migrate-job run, or when the user asks "how did the migration go", "what failed", "did it pass".

Review a migrated .ipynb for correctness — NOT just "did it run". Catches latent issues the cell-execute loop missed — wrong write-mode, lost rows, dropped columns, hardcoded paths, dead Databricks-isms, builtins shadowing, format downgrades. Outputs a structured Blockers / Important / Style / Good review report. Use after aidp-migrate-job completes, especially on the first few notebooks of a new workload before scaling out.

Guided full-job migration flow. Walks the user from "I want to migrate this Databricks job" through DAG → data check → migrate → status, asking before each phase. Composes aidp-build-dag, aidp-check-data, aidp-migrate-job, and migration-status. Use when the user wants the end-to-end guided experience instead of running individual phases manually.

Guided catalog migration flow. Extracts Databricks Unity Catalog / HMS metadata, previews the 18-rule DDL rewrite, then batched replay on AIDP. Asks before the destructive replay step. Use when the user wants to migrate the catalog layer (schemas + tables) with checkpoints, rather than running aidp-migrate-catalog directly.

Read a single Databricks notebook (.ipynb / .py / .scala source format) and produce a migration-readiness report — what it does, what it depends on, what risks the migrator will hit, which gotchas (from references/gotchas.md) will apply. Run before manually authoring an entry in a migration manifest, OR as a one-off "should we migrate this?" assessment. Read-only — does not modify the notebook and does not invoke the migrator.

Consume an OCI Streaming stream from an AIDP notebook via Spark structured streaming (Kafka-compat). Use when the user mentions OCI Streaming, Kafka on OCI, stream pool, structured streaming, or wants to read Kafka messages into Spark. Auth is SASL/PLAIN with an OCI auth token. Pattern matches the official Oracle AIDP sample.

Read or write Microsoft SQL Server from an AIDP notebook via the AIDP `aidataplatform` Spark format handler. Use when the user mentions SQL Server, MSSQL, or has a TDS host/port. Auth is host/port + database + user/password.

About 450 ready-made HyperFrames blocks and components installed as editable source - transitions, overlays, titles, kinetic type, captions, charts, map overlays, 3D, camera moves. Use it before hand-building any named visual (CRT scanlines, glitch, film grain, a chart); also for hyperframes add and catalog.

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.

Deprecated compatibility name for prisma-orm-setup. Use only when a user or existing integration explicitly invokes prisma-database-setup; otherwise select prisma-orm-setup.

Deprecated compatibility name for prisma-postgres-setup. Use only when a user or existing integration explicitly invokes prisma-postgres; otherwise select prisma-postgres-setup.

Obtain or reuse a Prisma Postgres database and connect an application. Use when the user needs a database and has none configured ("I need a database", "add a Postgres database", "set up a database for this app"), runs or mentions `create-db` or `npx create-db`, or asks to set up or connect Prisma Postgres, including in v0 and the Vercel Marketplace. Hands Prisma ORM configuration to prisma-orm-setup; reuses an existing connection first and honors an explicit provider, driver, alternative ORM, or database-only choice.

Required reference for Prisma ORM 7 SQL driver adapter work. Use when implementing or modifying adapters, adding database drivers, or touching SqlDriverAdapter, Transaction, savepoint, result mapping, or DriverAdapterError behavior. Covers current transaction lifecycle, optional savepoint hooks, original database-error preservation, and verification.

Diagnose and fix common FiftyOne issues automatically. Use when a dataset disappeared, the App won't open, changes aren't saving, MongoDB errors occur, video codecs fail, notebook connectivity breaks, operators are missing, or any recurring FiftyOne pain point needs solving.

Generate a Data Lens connector from an external database schema. Use when users want to connect an external data source (PostgreSQL, BigQuery, Databricks, MySQL, etc.) to FiftyOne Data Lens, or when they have a database schema and want to browse/import that data through the FiftyOne App.