convert

name	convert
description	Convert source code to Snowflake SQL using SnowConvert. Transforms full-migration sources and code-conversion-only sources to Snowflake-compatible syntax, and optionally repoints Power BI reports. Triggers: convert, snowconvert, transform code, convert to snowflake, power bi.

Code Conversion

On Entry

Tell the user:

Code Conversion.

Here's what I'll do:

1. Run SnowConvert against your source SQL files, which transforms each one into Snowflake SQL syntax.
2. Generate reports flagging anything that needs manual review (EWIs, FDMs, performance remarks, out-of-scope items).
3. Save converted code under snowflake/ and reports under reports/SnowConvert/.

Convert source code to Snowflake SQL using SnowConvert.

Prerequisites

• Migration project initialized (scai init)
• Source code present in the project source/ directory, either from extraction or scai code add

Workflow

Step 1: Verify Source Code Exists

Confirm source/ contains .sql files (use whichever portable form fits the host).

If no files are found, the setup state machine should have already routed back to register-code-units before you got here. If somehow you arrived with an empty source/, return to the parent setup skill so it can re-query next_setup_task.

Step 2: Check for ETL Code

Ask the user via ask_user_question (multiSelect = false):

"Do you have any ETL code (SSIS or Informatica Power Center) to include in the conversion?"

1. Yes
2. No

• If Yes, ask which platform (SSIS or Informatica).

  • If Informatica, present this recommendation before asking for the path:

    For the smoothest Informatica migration, we recommend exporting your workflows using Snowflake's official DDL Export Script. This produces one XML file per workflow in a consistent format that SnowConvert and the downstream stabilization skill are designed to read.

    Extraction guide: https://github.com/Snowflake-Labs/SC.DDLExportScripts/blob/main/ETL/Informatica%20PowerCenter/README.md

    Summary:

    1. pmrep connect -r <repo> -d <domain> -n <user> -x <password>
    2. python export_all_workflows.py --folder-name "<folder_name>"
    3. pmrep cleanup

    Output: ./exports/<workflow_name>.xml, one file per workflow.

    Then ask with ask_user_question:

    • "I already exported using this guide; proceed"
    • "I exported another way, but I'd like to proceed anyway"
    • "Let me re-export first; I'll provide the path when ready"

    On "re-export first", stop and wait for the user to return with the path. On either "proceed" option, continue to the filesystem path prompt below.

  • If SSIS, no extraction-guide prompt is needed, proceed directly to the filesystem path prompt below.

  • After platform handling, ask for the filesystem path where the ETL code is located. Store this path for Step 4.

  • If Informatica, after storing the ETL path, ask with ask_user_question (multiSelect = false):

    "Which conversion target for Informatica PowerCenter?

    1. dbt — mappings convert to dbt models orchestrated by Snowflake Tasks
    2. scripting — mappings convert to Snowflake stored procedures (Snowflake Scripting)"

    Call the MCP configure tool with etl_informatica_target set to "dbt" or "scripting" so it persists to .scai/config/plugin.yml for downstream use by the conversion CLI and assessment output.

• If no, proceed to Step 3; no <ETL_PATH> will be set.

Step 3: Check for Power BI Reports

Ask the user:

"Do you have Power BI reports (.pbit files) you'd like to repoint to Snowflake?"

If yes, load ../powerbi-repointing/SKILL.md. It collects PBIT_PATH and tells you to append --powerbi-repointing <PBIT_PATH> to the convert command in Step 4. Return here when complete.

If no, proceed to Step 4. PBIT_PATH remains unset; do not pass --powerbi-repointing to scai.

Step 4: Run Conversion

Before running, tell the user what the conversion will cover: mention ETL if ETL_PATH was set, and Power BI repointing if PBIT_PATH was set.

Always include --json so the agent can parse the result envelope. Append --etl-replatform-sources-path <ETL_PATH> and/or --powerbi-repointing <PBIT_PATH> only if those paths were set.

No ETL:

scai code convert --json

With ETL:

scai code convert --etl-replatform-sources-path <ETL_PATH> --json

Substitute the bracketed tokens with the actual paths you stored. Do not emit literal <ETL_PATH> or <PBIT_PATH> to the shell.

Step 5: Review Results

Conversion produces:

• Converted code in snowflake/
• Reports in reports/SnowConvert/
• Logs in logs/

Key metrics to check:

• Files Processed
• Code Units Converted (LOC)
• Conversion Errors (should be 0)
• EWIs (Early Warning Issues), especially high/critical

Conversion Options

Option	Description
-x, --show-ewis	Show detailed EWI breakdown
--overwrite-working-directory	Overwrite output files in snowflake/ and registry
--etl-replatform-sources-path <PATH>	Path to ETL code (SSIS or Informatica) for conversion

For Power BI options, see ../powerbi-repointing/SKILL.md.

Example with options:

scai code convert --show-ewis --overwrite-working-directory --json

Understanding EWIs

EWIs (Early Warning Issues) indicate conversion items needing attention:

Severity	Action Required
Critical	Must fix before deployment
High	Should fix, may cause runtime errors
Medium	Review recommended
Low	Minor issues, optional fixes

Common EWI codes:

• SSC-EWI-0030: Dynamic SQL (requires manual review)
• SSC-FDM-*: Functional differences (behavior may differ)
• SSC-PRF-*: Performance remarks (optimization suggested)

Output Structure

snowflake/
├── <database>/
│   └── <schema>/
│       ├── table/
│       ├── view/
│       ├── procedure/
│       └── function/
artifacts/
├── ETL/                               # Converted ETL code (tasks, dbt models, etc.)
│   └── <package_name>/
│       ├── <package_name>.sql         # Snowflake tasks
│       └── <data_pipeline>/
│           └── models/                # dbt models (staging, intermediate, marts)
reports/
├── SnowConvert/
│   ├── TopLevelCodeUnits.*.csv
│   ├── Issues.*.csv
│   ├── ObjectReferences.*.csv
│   ├── Assessment.*.json
│   ├── ETL.Elements.*.csv             # ETL elements processed (packages, tasks, data flows)
│   └── ETL.Issues.*.csv               # ETL-specific conversion issues
├── ArrangeReports/
└── GenericScanner/
logs/

For Power BI output paths, see ../powerbi-repointing/SKILL.md.

CHECKPOINT

Confirm with user:

• Conversion completed without errors
• Review EWI summary (especially high/critical count)
• Converted files appear in snowflake/
• If ETL code was included: ETL packages processed successfully, ETL issues reviewed, and converted ETL code appears in artifacts/ETL/
• If Power BI reports were included, follow the CHECKPOINT addendum in ../powerbi-repointing/SKILL.md

On Completion

After the CHECKPOINT passes, tell the user. Fill placeholders from the JSON envelope returned by scai code convert --json.

Conversion complete. <filesProcessed> files / <codeUnitsConverted> code units converted in <duration>.

Issues found: <total> instances total • EWIs: <ewi.total> instances across <ewi.unique> codes (<critical> critical, <high> high, <medium> medium, <low> low) • FDMs (functional differences): <fdm.total> instances (omit line if 0) • PRFs (performance remarks): <prf.total> instances (omit line if 0) • OOS (out-of-scope): <oos.total> instances (omit line if 0)

If etlReplatforming is present: ETL: <etl.processedFiles> files, <etl.totalIssues> issues. Critical EWIs require manual fix before deploy. Reports in reports/SnowConvert/.

Next, we'll run an assessment to plan your migration: dependency waves, object categorization, and a deployment plan.

Then return to the calling skill.