Migrate a Snowflake database to Oracle AI Data Platform with a fixed, auditable runbook. Provisions a migration workspace and cluster, registers the Snowflake database as an EXTERNAL catalog and creates the INTERNAL target catalog, discovers the estate with an in-AIDP workflow, translates types and names into a reviewed plan, creates the target schemas and empty Delta tables on AIDP compute, and registers one copy job per schema (INSERT-SELECT, verified by row counts) for the customer to run. Inventories what is not a table or a view, security posture and table-maintenance state, and presents the data-movement options without choosing for you. Read-only against Snowflake, dry-run by default against AIDP, every create read back; teardown releases the compute or removes everything the migration created.
Plugin oracle-ai-data-platform-workbench-snowflake-migrator in oracle-samples/oracle-aidp-samples. Commands read from the repo's manifest — today.
snowflake-assess-estateRead-only PREVIEW of a Snowflake environment from the operator's machine - inventory of tables and views with row counts, byte sizes and column types, plus the census of objects that are not tables or views, table-maintenance state and security posture. Use ONLY when the user wants to look at an acc
snowflake-clone-notebookGenerate the table-creation script for a Standard AIDP catalog as an executable notebook, locally and offline. --upload is a dry run and is refused with --execute; the structure itself is created by the snowmig_01_structure workflow at S10. The script creates schemas, then tables, then views in depe
snowflake-compute-proposalMap Snowflake warehouses onto AIDP Spark compute clusters and produce a sizing and cost proposal. Inventories every warehouse with its size, multi-cluster scaling policy and auto-suspend, pulls observed credit consumption from ACCOUNT_USAGE where permitted, and proposes worker counts and autoscale c
snowflake-medallion-cloneCreate the medallion architecture on Oracle AI Data Platform - registering an EXTERNAL catalog of source type SNOWFLAKE by default, and generating Spark SQL for schemas, tables and views from an approved Snowflake plan only when the user has explicitly asked for a Standard catalog. This stage copies
snowflake-migration-planBuild a high-level Snowflake to AIDP migration plan and present it for approval. States which objects can migrate and which cannot with a brief reason for each, applies user-supplied restrictions such as excluded databases or size caps, derives dependency order so views follow their base tables, and
snowflake-migrator-bootstrapFirst-run setup for the Snowflake to AIDP migrator. Finds or creates the one migration config file (snowmig-config.yaml), reads every field back with secrets masked, verifies Snowflake authentication by password, key-pair, programmatic access token or SSO, verifies the AIDP end, then smoke-tests the
snowflake-migrator-demoDev mode. Run the entire Snowflake-to-AIDP migration pipeline against a built-in emulated estate and an emulated AIDP — no credentials, no network, nothing real is touched. Use when the user wants to understand what the migrator does before pointing it at a real account, wants a training walkthrough
snowflake-migrator-overviewRouter, runbook and shared rules for migrating a Snowflake estate onto Oracle AI Data Platform (AIDP). Read this first whenever the user mentions migrating, moving, assessing, inventorying or cloning Snowflake databases, schemas, tables, views or warehouses onto AIDP, asks to "run the migration" or
snowflake-provision-environmentProvision the migration environment inside AIDP for the prod flow - the workspace (name auto-translated to the simplest safe charset), the migration-assets compute cluster, optional cluster libraries from requirements-aidp.txt, the backup-snowflake-migration/ workspace folder holding the data-migrat
snowflake-smoke-testCheck connectivity and permissions on both ends before any migration work. Verifies Snowflake is reachable and readable (list databases, read INFORMATION_SCHEMA) and, when AIDP coordinates are supplied, that the target catalog is readable and optionally writable. Use before the first assessment, whe
snowflake-stage-boardShow the Snowflake-to-AIDP migration as a stage table before running it - which stages are supposed to run, which have run, and what each one found, with the writing stages marked. Use when the user asks what the plugin will do, what stage comes next, where a run got to, why something was skipped, o
/oracle-ai-data-platform-workbench-snowflake-migrator:snowflake-assessInvestigate a Snowflake environment and list every table and view with row counts (Snowflake's metadata count by default), sizes, and column types. Read-only.
/oracle-ai-data-platform-workbench-snowflake-migrator:snowflake-catalogRegister the target catalog on AIDP — EXTERNAL/SNOWFLAKE by default, a read-only pointer at the live source that copies nothing. Dry-run first; --execute only after showing the user exactly what will be registered.
/oracle-ai-data-platform-workbench-snowflake-migrator:snowflake-computeMap Snowflake warehouses to AIDP Spark clusters and produce a sizing and cost proposal.
/oracle-ai-data-platform-workbench-snowflake-migrator:snowflake-demoDev mode — run the whole migration pipeline against an emulated Snowflake estate and an emulated AIDP. No credentials, no network, nothing real is touched; writes every real artifact plus a narrated DEMO.md.
/oracle-ai-data-platform-workbench-snowflake-migrator:snowflake-notebookGenerate the shallow-clone notebook locally (offline) for a Standard catalog the user explicitly asked for. --upload is a dry run and is refused with --execute; the structure itself is created by `snowmig run --job snowmig_01_structure` at S10.
/oracle-ai-data-platform-workbench-snowflake-migrator:snowflake-planBuild and present a high-level Snowflake to AIDP migration plan - dependency waves plus a proposed medallion layout - for approval.
/oracle-ai-data-platform-workbench-snowflake-migrator:snowflake-provisionProvision the AIDP migration environment - workspace (name auto-translated), migration-assets cluster, cluster libraries, the backup-snowflake-migration/ folder with scripts and plan, and the migration jobs (discover, structure, reconcile, and one copy job per schema of the approved plan, passing sc
/oracle-ai-data-platform-workbench-snowflake-migrator:snowflake-smokeCheck Snowflake and AIDP connectivity and permissions before migrating. Read on the source, read/write on the destination.
/oracle-ai-data-platform-workbench-snowflake-migrator:snowflake-soft-cloneCreate the target catalog and medallion structure on AIDP from an approved plan. Registers an EXTERNAL/SNOWFLAKE catalog by default; a Standard catalog at runbook S4 or when you ask for one, its structure created on AIDP compute.
Run the full Oracle AI Data Platform (AIDP) data-engineering surface from Codex in natural language - 37 skills: discover catalog, ask in English, AI-in-SQL, optimize/time-travel, pipelines, clusters, governance, agent flows, MLOps, migration. Self-contained (OCI CLI + api_key DEFAULT profile); the AIDP MCP is an optional accelerator.
37 skills · hooks
Oracle AI Data Platform Workbench Spark connectors for Codex. Includes 27 connector skills for Oracle, OCI, SaaS, JDBC, object storage, streaming, REST, Excel, and multi-cloud data sources, including DB2 guidance. Includes Google BigQuery read-only ingestion and external-catalog guidance.
29 skills
Build and operate Oracle Fusion-to-AIDP medallion pipelines, gold marts, OAC datasets, and MCP-authored workbooks.
16 skills · 1 MCP server
Drive the Oracle AI Data Platform (AIDP) Databricks Migration Toolkit in natural language. Self-contained for Codex: the OpenAI-based Python migration engine ships bundled under engine/ and is staged by the SessionStart hook to ~/.aidp-migrator/engine. Teaches Codex how to plan and execute an automated end-to-end migration of Databricks (Unity Catalog / HMS) notebooks, jobs, schedules, and catalog DDL onto AIDP - Pass-1 dependency resolution plus Pass-2 cell-by-cell execute/verify/fix on a live AIDP cluster using an OpenAI model with tool use. Covers job_migrate.py orchestration, catalog migration, workflow DAG manifest building, fixup_cell rewind, pre-migration data-availability checks, write-redirect sandbox schema, and the acceptance-contract pattern for batch/streaming convergence.
16 skills · hooks
Migrate Informatica ETL onto Oracle AI Data Platform from Codex: mappings become PySpark notebooks, workflows become AIDP jobs carrying the session dependency graph, Quartz schedules and a declarable timezone, with worklets expanded. Reads IDMC/IICS cloud mapping JSON and PowerCenter 10.x repository XML; 8.x and 9.x are refused by a version gate rather than mis-migrated. The transformation compiler is deterministic and needs no model -- an OpenAI key only widens what the rules cannot reach, behind a validator and a hallucination check. Reads and writes are catalog-addressed, so no JDBC URLs or credentials appear in a generated notebook. Anything that cannot be converted faithfully becomes an explicit review item with a named reason and a rebuild path, never a silent approximation.
11 skills · hooks
Migrate a Microsoft Fabric workspace (notebooks, Warehouse T-SQL, OneLake shortcuts) to Oracle AI Data Platform: inventory, plan, translate deterministically, and verify.
1 skill · 5 commands · 1 MCP server
Matt Pocock's agent skills for real engineering (grilling, spec/ticket flows, TDD, code review, domain modelling and more).
39 skills
AGENTS.md as project instructions, by one option. Under claude-md-or-agents-md a project with no instruction files of its own gets its AGENTS.md files instead: a prompt.context hook asks $.fs.ancestors for every AGENTS.md and .claude/AGENTS.md from the filesystem root down to the working directory and hands them to the engine as project instruction files, which it renders, announces and withholds from agents exactly as it does CLAUDE.md, skipping any file the engine already loaded by import or link; a tool.call hook on Read attaches the ones under the project root as the engine attaches a nested CLAUDE.md. Under claude-md-and-agents-md every AGENTS.md is loaded beside CLAUDE.md. Under managed-only the project's and the person's instruction files are dropped and the organization's managed ones kept. Under claude-md the engine's walk stands alone. claude-md-or-agents-md is the default.
Production-grade engineering skills covering every phase of software development: spec, plan, build, verify, review, and ship.
25 skills · 4 agents
Agentic QE (external: maintained in proffesor-for-testing/agentic-qe, pinned to v3.15.17): a quality-engineering fleet with 11 QE agents, 9 skills, 9 commands, the agentic-qe MCP server pinned to the plugin version, and the aqe-mod guard that refuses destructive operations on AQE learning data
9 skills · 9 commands · 11 agents · 1 MCP server
Framework updates, migration planning, and architectural transformation workflows
4 skills · 3 commands · 2 agents
Long-term semantic memory for Claude Code, powered by OpenViking
5 skills · 1 command · 1 MCP server · hooks
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