Oracle AI Data Platform Workbench Engineer Agent plugin for Claude

Build AIDP agents in high-code Python with aidputils + LangGraph (the code-first alternative to the low-code agent-flow canvas). Use when the user wants to write an agent in Python, use LangGraph / create_react_agent…

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…

Answer 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 .ai…

Manage and search AIDP audit logs — enable/disable auditing, set retention, and query audit-log entries for a DataLake. Use when the user asks about audit logging, who did what, compliance/retention of AIDP activity,…

Deploy AIDP resources as a bundle — create a bundle, deploy all its assets atomically, query deployment status, and purge. Use when the user wants to promote/deploy a set of AIDP resources together, manage a deploymen…

Browse the AIDP data catalog live — list catalogs, schemas, tables, and volumes, inspect a table's columns/properties, and resolve a human name to its catalog key. Use when the user asks "what catalogs/schemas/tables…

One-time AIDP catalog discovery that writes a cached, version-controllable .aidp/catalog.md grounding file (tables, columns, FK/join hints, value dictionaries). Use when the user says "/aidp-catalog-init", asks to "ma…

Manage AIDP Spark compute clusters — list, status, start/stop/restart, installed libraries (JARs/Python), provision/scale a new cluster (driver/worker shapes, autoscale, GPU/RAPIDS, AI Compute), and connect external B…

Manage the AIDP credential store (secrets) — list, get, create, update, delete credentials used by AIDP workflows. Use when the user wants to store/rotate a secret centrally instead of embedding it, or manage connecti…

Run data-quality rule checks on AIDP tables — not-null, uniqueness, allowed ranges/sets, referential integrity, and freshness. Use when the user wants to validate data, check for nulls/duplicates/orphans, assert a col…

Share AIDP data via Delta Sharing — create/manage shares, add data assets, manage recipients, and grant access/permissions. Use when the user wants to share a table/schema with another team or org, set up Delta Sharin…

First-run setup for the self-contained AIDP plugin. Verifies the oci CLI + a DEFAULT api_key profile, installs the bundled Python deps, discovers region + DataLake OCID + workspace, then smoke-tests both engines (a co…

Router + setup/auth troubleshooting for Oracle AI Data Platform (AIDP) data-engineering work. Use when the user mentions AIDP and isn't sure which skill applies, asks "what can you do with AIDP", describes a task by c…

Federate across multiple data sources in one AIDP Spark session — read from several connectors (Oracle ADB/ExaCS, Fusion, Snowflake, S3, lakehouse tables, …) and join them in a single notebook. Use when the user wants…

Operate native Git in an AIDP workspace — branches, checkout, commit/push, pull, merge, rebase, reset, diff, and conflict resolution on workspace git repositories. Use when the user wants to version workspace notebook…

Load a data file (CSV/JSON/Parquet/etc.) into a managed AIDP Delta table. Use when the user wants to ingest a file into a table, create a table from a file, or land raw data in the lakehouse. Supports the 1-step path…

Build and manage AIDP Knowledge Bases for RAG — create a KB over catalog data, pick an embedding model + chunking, build an HNSW/IVF vector index, add data sources (volume/table), run ingestion jobs, and manage KB per…

Guide a migration of notebooks/jobs from another platform (e.g. Databricks) into AIDP. Use when the user wants to port Databricks notebooks/jobs to AIDP, move workloads onto the AIDP lakehouse, or plan a migration. Or…

Track ML work in AIDP's MLflow-compatible MLOps — experiments, runs, metrics/params, registered models, and model versions. Use when the user wants to log/track experiments, list runs or metrics, register a model, tra…

List the models available/installed in the AIDP DataLake and inspect their parameters, and browse the MLOps model registry. Use when the user asks "what models are available", needs a model name for ai_generate()/agen…

Create, edit, and execute AIDP notebooks and manage their kernel sessions. Use when the user wants to author a notebook, run cells/code on a cluster, attach/detach a kernel session, or build an interactive notebook (e…

Surface AIDP operational state — recently accessed resources and long-running async operations (status, completion, waiting). Use when the user asks "what happened recently", "what's running", "is that operation done…

Author, schedule, run, and monitor AIDP Jobs (task DAGs of notebooks/python with cron). Use when the user wants to build a pipeline, create/update/run a Job, schedule a recurring run, check a run's status, read a task…

Profile an AIDP table — row count, per-column null %, distinct count, min/max/mean, and top-K values. Use when the user asks to profile a table, wants column statistics or a data-quality snapshot, or needs to understa…

Manage AIDP roles and access — list roles, view permissions, create roles, add/remove members, and grant/revoke per-resource permissions on catalogs, schemas, tables, views, volumes, workspaces, workspace objects, and…

Maintain a semantic grounding 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/busines…

Diagnose slow or failed AIDP Spark work using cluster logs, metrics, and the Spark UI REST API. Use when a job/query is slow or failed, the user asks "why did this fail / why is it slow", or you need stage/task timing…

Use when a Spark job/notebook is slow, missing an SLA, spilling, OOMing, generating too many small files, or shuffling/skewing heavily; when reviewing Spark/PySpark code or a Spark UI for performance; or before runnin…

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…

Control-plane lifecycle for AIDP catalog objects — create/update/delete/refresh tables, views, schemas, and catalogs, and register an EXTERNAL catalog/connection (ALH/ADW/object-storage) as a persistent catalog object…

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…

Manage AIDP user settings / preferences — list, get, create, update, delete a user's settings for the DataLake. Use when the user wants to view or change their AIDP workbench preferences/settings, or manage stored use…

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 ver…

Work with AIDP volumes — list volumes, browse files inside a volume, upload/download via the PAR flow, and create directories. Use when the user mentions volumes, needs to stage large/binary files, or move data in/out…

Provision and inspect AIDP DataLake instances and workspaces, including private-network workspaces attached to a customer VCN/subnet. Use when the user wants to create/list/get a workspace or DataLake instance, set up…

Manage files and notebooks in the AIDP workspace filesystem — list, upload, download, read, create, move, rename, delete files/folders/notebooks. Use when the user wants to put a script/notebook/config into the worksp…