dms-schema-conversion

Files (6)

• SKILL.md
• action-items.md · references/
• cancel-operations.md · references/
• schema-conversion-operations.md · references/
• setup-wizard.md · references/
• troubleshooting.md · references/

SKILL.md (first lines)

# 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](https://docs.aws.amazon.com/dms/latest/userguide/sc-selection-rules.html) — scoping operations to specific objects
- [Transformation rules in DMS Schema Conversion](https://docs.aws.amazon.com/dms/latest/userguide/sc-transformation-rules.html) — 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.
- You MUST set the `AWS_EXECUTION_ENV` environment variable to `AWSMCP-DMSSchemaConversion-Skill` before running any AWS CLI command in this skill, so that calls made during this agentic workflow are attributable in the CloudTrail `userAgent` field. The AWS CLI and botocore append this value to the request User-Agent as `exec-env/AWSMCP-DMSSchemaConversion-Skill`. Set it once for the session (`export AWS_EXECUTION_ENV=AWSMCP-DMSSchemaConversion-Skill`) or prefix each command (`AWS_EXECUTION_ENV=AWSMCP-DMSSchemaConversion-Skill aws dms ...`). The value is a best-effort attribution marker only — it is not an access control, and it MUST contain no spaces so it stays a single User-Agent token.

---

## 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](#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](#actions-menu).
- **If no projects exist** → ask: "No migration projects found. Would you like to create one?" If yes, load [setup-wizard.md](references/setup-wizard.md) and run the full setup wizard from Phase 1. After wizard completes, run [Auto Import](#auto-import), then proceed to [Actions Menu](#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](https://docs.aws.amazon.com/dms/latest/userguide/sc-selection-rules.html) for JSON format.

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

3. 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).

4. **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?"

5. Proceed to [Actions Menu](#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_").

2. **Build selection rules:** Translate the customer's natural language to selection rules JSON. Refer to [Selection rules in DMS Schema Conversion](https://docs.aws.amazon.com/dms/latest/userguide/sc-selection-rules.html) for format, wildcards, and vendor-specific locators.

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

4. **Wait for completion:** Wait using the DMS waiter:

   ```
   aws dms wait metadata-model-converted \
     --migration-project-identifier <migration_project_identifier> \

From aws/agent-toolkit-for-aws, Apache-2.0.

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