Dms Schema Conversion

DMS Schema Conversion

Overview

This skill handles the full DMS Schema Conversion lifecycle — from first-time setup to running conversions on an existing project.

The AWS MCP server is recommended for streamlined execution, audit logging, and observability. When the MCP server is not available, all operations can be performed via AWS CLI directly.

Key documentation:

• Selection rules in DMS Schema Conversion — scoping operations to specific objects
• Transformation rules in DMS Schema Conversion — renaming schemas, tables, columns during conversion

Global constraint: You MUST fetch and read any linked documentation before acting on it — do NOT rely on memory for any referenced material (selection rules, transformation rules, troubleshooting guides, network configuration, etc.). Documentation contains vendor-specific details that change between engines and API versions.

Guardrail — where this skill's own files live (MCP vs local install)

This skill can be loaded two ways, and they resolve the skill's own bundled files from different places. Determine how the skill was loaded before reading a reference:

• Loaded through the AWS MCP `retrieve_skill` tool: The skill is not installed on the local filesystem. You MUST fetch each reference via retrieve_skill with the file parameter (e.g. file="references/setup-wizard.md"). Do NOT file_read these paths locally — they do not exist on disk.
• Installed locally (e.g. .kiro/skills/dms-schema-conversion/ or ~/.claude/skills/dms-schema-conversion/): Read files from the local skill directory using relative paths.

This distinction applies only to the skill's own packaged files. User data and session artifacts are always read from and written to the user's working directory. Never fetch or write customer data through retrieve_skill.

Verify Dependencies

Before starting, check that AWS CLI commands can be executed.

Constraints:

• You MUST verify that AWS CLI commands can be run (via MCP server tools or directly via shell)
• You MUST inform the customer if no execution method is available and ask whether to proceed
• You MUST ask the customer which AWS region to use — do NOT attempt to infer it from the STS response (it does not contain a region field). If the customer is unsure, suggest checking the AWS_DEFAULT_REGION environment variable or the --region flag they are using.

Project Selection

Check for existing migration projects:

aws dms describe-migration-projects

• If exactly one project exists → ask the customer: "Found migration project <name>. Would you like to use it, or create a new one?" If they confirm, store migration_project_identifier and proceed to Actions Menu. If they want a new one, run the setup wizard.
• If multiple projects exist → list them and ask the customer to pick one, or offer to create a new project. Store migration_project_identifier, proceed to Actions Menu.
• If no projects exist → ask: "No migration projects found. Would you like to create one?" If yes, load setup-wizard.md and run the full setup wizard from Phase 1. After wizard completes, run Auto Import, then proceed to Actions Menu.

Auto Import

This section runs only after the setup wizard creates a new project. Do NOT run for existing projects.

1. Build selection rules to import all schemas from the source server. For server-name, use the data provider identifier (the short ID from the ARN, e.g., JIFET2LUZJEJZPDYSOSGANOA2M) or the literal ServerName value from the data provider settings (e.g., "offline" for offline sources). For SQL Server, you MUST include database-name in the object locator. See Selection rules in DMS Schema Conversion for JSON format.

1. Run start-metadata-model-import with --origin SOURCE --refresh and the selection rules from step 1. Extract RequestIdentifier from the response.

1. Wait for import completion using the DMS waiter:

   aws dms wait metadata-model-imported \
     --migration-project-identifier <migration_project_identifier> \
     --filter 'Name=schema-conversion-operation-id,Values=<RequestIdentifier>'

If the waiter fails or is unavailable, fall back to polling describe-metadata-model-imports every 30 seconds with --filter Name=request-id,Values=<RequestIdentifier>. Terminal statuses: SUCCESS (proceed) or FAILED (check error via the Error field in the response).

1. Show discovered schemas: On success, call describe-metadata-model-children with --origin SOURCE at the root level to list the imported schemas/databases. Present the discovered names to the customer so they can confirm the correct database connection was established: > "Import complete. I found the following schemas/databases: <list>. Does this look correct?"

1. Proceed to Actions Menu.

Actions Menu

Present the actions menu using a structured selection tool (e.g., AskUserQuestion) if available — this gives the customer a clickable/selectable list.

For SQL Server → PostgreSQL/Aurora PostgreSQL projects (present as a single-select question "What would you like to do?"):

1. Convert database — convert schema objects to the target engine (also produces an conversion assessment report)
2. Assess database — run a compatibility assessment (also produces an conversion assessment report)
3. Convert statement — convert a single SQL statement
4. Clean up — delete migration project and related DMS resources

For all other engine combinations (present as a single-select question "What would you like to do?"):

1. Convert database — convert schema objects to the target engine (also produces an conversion assessment report)
2. Assess database — run a compatibility assessment (also produces an conversion assessment report)
3. Work with tree — browse the metadata model tree
4. Clean up — delete migration project and related DMS resources

The customer can always type a custom request via "Other" (e.g., "work with tree", "show database statistics", or "exit"). If the customer selects "Other" and describes an action covered by this skill, handle it accordingly.

After each action completes, return to this menu by presenting the same selection again.

Note on metadata loading: start-metadata-model-import (with Refresh=false), start-metadata-model-assessment, and start-metadata-model-conversion all load the source tree for the scoped objects. If metadata was already imported in the current session for a given subtree, it does not need to be re-imported — these operations will work with what is already loaded.

Convert Database

1. Ask what to convert: Ask the customer what they want to convert (e.g., "all schemas", "schema public", "tables starting with PROD_").

1. Build selection rules: Translate the customer's natural language to selection rules JSON. Refer to Selection rules in DMS Schema Conversion for format, wildcards, and vendor-specific locators.

1. Run conversion: Call start-metadata-model-conversion with the migration project and selection rules. Extract RequestIdentifier from the response.

1. Wait for completion: Wait using the DMS waiter:

   aws dms wait metadata-model-converted \
     --migration-project-identifier <migration_project_identifier> \
     --filter 'Name=schema-conversion-operation-id,Values=<RequestIdentifier>'