aidp-migrate-job

Build 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 lists the Silver and Gold job stubs. Use after an estate assessment, or when the user asks what can be migrated, in what order, why something is excluded, or wants to see the migration plan.

Router, 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 "start from zero", or asks what a Snowflake migration would involve. Carries the FIXED twelve-step order of operations and the rules that apply at every step; adds no API surface of its own.

Dev 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, or asks "show me how this works" / "demo mode" / "dev mode". Produces every real artifact plus DEMO.md, a narrated walkthrough of the lessons.

First-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 connection and reports the account, region, role and warehouse. Use the first time the migrator runs on a machine, or when any other stage fails with an authentication, connection or "no config found" error.

Map 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 ceilings per warehouse. Use when the user asks about compute sizing, warehouse equivalence, cluster shapes, credits, or what the migration will cost.

Generate 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 dependency order, prints per-object progress with elapsed time so a long run stays visible, and verifies each object individually at the end. This script creates structure only and copies no data - every table arrives with zero rows; rows are copied only by the snowmig_02_copy_schema job, when the operator runs it. Use when the user has explicitly asked for a Standard catalog, or wants the migration delivered as a runnable script rather than executed straight from the CLI.

Provision 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-migration scripts and the plan artifacts, and the migration jobs (discover, structure, reconcile, plus one copy job per schema of the approved plan, each passing its schema as a task parameter). Use when the user wants to set up AIDP for the migration, upload the migration scripts, create the migration workspace or cluster, or wire the migration jobs. Dry-run by default.

Create 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 no data - rows are copied only by the snowmig_02_copy_schema job, when the operator runs it. Use when the user asks to create the medallion structure, soft clone, shallow clone, create the target catalog, or deploy the target schema.

No description in the SKILL.md.

No description in the SKILL.md.

No description in the SKILL.md.

No description in the SKILL.md.

飞书多维表格（Base）操作：建表、字段、记录、视图、统计、公式/lookup、表单、仪表盘、应用模式（BaseApp/AppMode 页面与组件）、Workspace 目录、workflow、角色权限、模板中心（多维表格模板分类/列表/搜索）；遇到 Base/多维表格/bitable、BaseApp/AppMode、/base/ 或 /app/ 链接时使用。BaseApp 不走 lark-apps；文件导入/导出转 lark-drive，认证/授权转 lark-shared。

Use for lark-cli setup/auth tasks: auth login/status/logout, user vs bot identity, business-domain permissions (--domain, including all/docs/drive), missing scopes, revoking authorization, or handling _notice JSON.

飞书知识库：管理知识空间、空间成员和文档节点。创建和查询知识空间、查看和管理空间成员、管理节点层级结构、在知识库中组织文档和快捷方式。当用户需要在知识库中查找或创建文档、浏览知识空间结构、查看或管理空间成员、移动或复制节点时使用。当用户给出 doubao.com 的 /wiki/ URL/token 时，也应直接使用本 skill，不要因为域名不是飞书而回退到 WebFetch；路由依据是 URL 路径模式和 token，而不是域名。不负责：上传文件到知识库节点下（走 lark-drive）、编辑文档/表格/Base 内容（走 lark-doc / lark-sheets / lark-base）。

飞书任务：管理任务、清单和任务智能体。创建待办任务、查看和更新任务状态、拆分子任务、组织任务清单、分配协作成员、上传任务附件、注册或注销任务智能体、更新任务智能体的主页数据、写入智能体任务记录。当用户需要创建待办事项、查看任务列表、跟踪任务进度、管理项目清单或给他人分配任务、为任务上传附件文件、注册注销任务智能体、更新智能体主页数据、写入任务记录时使用。