SnowConvert AI CLI (scai) Command Reference¶

scai project info¶

Display project details including name, source language, and status.

scai project info

Prerequisites:

• Must be run from within a migration project directory.

Output fields: Project Name, Project ID, Source Language, Snowflake Connection, Project Root.

Examples:

scai project info

scai project set-default-connection¶

Set the default Snowflake connection for the current project.

scai project set-default-connection -c <CONNECTION>

Prerequisites:

• A migration project initialized with scai init.

• Snowflake connection available in connections.toml or config.toml.

Options:

Connection precedence:

1. -c/--connection option (per-command override)

2. Project connection (set by this command)

3. Default TOML connection

Examples:

# Set project default connection
scai project set-default-connection -c my-snowflake

# Change to production connection
scai project set-default-connection -c prod-snowflake

scai connection add-sql-server¶

Add a new SQL Server source database connection.

scai connection add-sql-server [OPTIONS]

Prerequisites:

• Network access to the SQL Server instance.

• For Windows auth: valid domain credentials.

• For standard auth: SQL Server username and password.

Authentication methods: Windows Authentication (Integrated Security), Standard Authentication (username/password).

Operation modes: Interactive (prompts for all required information – recommended) or Inline (command-line options for automation/CI).

Connections are saved to ~/.snowflake/connections.toml (or project-local).

Options:

Examples:

# Add connection interactively (recommended)
scai connection add-sql-server

# Windows Authentication
scai connection add-sql-server --connection my-sqlserver --auth windows --server-url localhost --database mydb

# Standard Authentication
scai connection add-sql-server --connection my-sqlserver --auth standard --server-url localhost --database mydb --username sa

scai connection add-redshift¶

Add a new Redshift source database connection.

scai connection add-redshift [OPTIONS]

Prerequisites:

• Network access to the Redshift cluster/serverless endpoint.

• For IAM auth: AWS credentials configured (AWS CLI or environment variables).

• For standard auth: username and password.

Authentication methods: IAM Serverless (AWS IAM with Redshift Serverless), IAM Provisioned (AWS IAM with Provisioned Cluster), Standard (username/password).

Operation modes: Interactive (recommended) or Inline (for automation/CI).

Connections are saved to ~/.snowflake/connections.toml (or project-local).

Options:

Examples:

# Add connection interactively (recommended)
scai connection add-redshift

# IAM Serverless (inline)
scai connection add-redshift --connection my-redshift --auth iam-serverless \
  --workgroup my-workgroup --database mydb --region us-east-1

scai connection set-default¶

Set the default source connection for a database type.

scai connection set-default -l <LANGUAGE> -c <CONNECTION>

Prerequisites:

• Connection already added with scai connection add-redshift or scai connection add-sql-server.

Options:

Examples:

# Set default Redshift connection
scai connection set-default -l redshift --connection prod

# Set default SQL Server connection
scai connection set-default -l sqlserver --connection dev

scai connection list¶

List connections for a given source database.

scai connection list [-l <LANGUAGE>]

Options:

Output: Table with columns: Name, Default, Host, Database.

Examples:

# List all connections summary
scai connection list

# List Redshift connections
scai connection list -l redshift

# List SQL Server connections
scai connection list -l sqlserver

scai connection test¶

Test a source database connection.

scai connection test -l <LANGUAGE> [-c <CONNECTION>]

Prerequisites:

• Connection already configured.

• Network access to the database.

Options:

Examples:

# Test SQL Server connection
scai connection test -l sqlserver -c my-sqlserver

# Test Redshift connection
scai connection test -l redshift -c my-redshift

scai code add¶

Add source code from an input file or directory to the project’s source/ folder.

scai code add -i <INPUT_PATH> [--skip-split] [OPTIONS]

Prerequisites:

• A migration project initialized with scai init.

• Input must be a valid SQL source file or a directory containing SQL source files.

Options:

Behavior notes:

• SQL Server and Redshift: runs arrange-only, produces artifacts/source_raw_Processed/, merges into source/.

• Other languages: copies source directly into source/.

• Checks for conflicting files when destination folders are non-empty (unless --overwrite is set).

Examples:

# Add source code to project
scai code add -i /path/to/source/code

# Add pre-split source code (skip arrange phase)
scai code add -i /path/to/source/code --skip-split

# Add a single file
scai code add -i /path/to/script.sql

# Add code overwriting existing files
scai code add -i /path/to/source/code --overwrite

# Add code with a source identifier for traceability
scai code add -i /path/to/source/code --source-id prod-sql-server-01

scai code extract¶

Extract code from the source database.

scai code extract [OPTIONS]

Supported languages: SQL Server, Redshift.

Prerequisites:

• A migration project initialized with scai init.

• Source database connection configured (use scai connection add-redshift or scai connection add-sql-server).

• Network access to the source database.

Options:

Interactive mode:

Requires an interactive terminal. In non-interactive or CI environments, use --schema, --object-type, and --name instead.

• Pre-fetch phase: prompt for schema (or leave empty for all) and multi-select object types to scope the catalog query.

• Post-fetch phase: multi-select schemas to include, optional name filter (wildcard * supported), summary table, then confirm extraction.

Options --schema, -t/--object-type, and -n/--name pre-fill the interactive prompts when used with -i.

Output structure:

source/
  └── <database>/
      └── <schema>/
          └── <type>/
              └── *.sql

Examples:

# Interactive extraction (browse and select)
scai code extract -i

# Interactive with pre-filled schema
scai code extract -i --schema public

# Extract tables from a schema
scai code extract --schema public --object-type TABLE

# Extract tables and views
scai code extract --object-type TABLE,VIEW

# Extract from all schemas
scai code extract

# Extract code with a custom source identifier
scai code extract --source-id prod-redshift-cluster

scai code convert¶

Transform source database code to Snowflake SQL.

scai code convert [OPTIONS]

Prerequisites:

• A migration project initialized with scai init.

• Source code in the source/ folder (from scai code extract, scai code add, or manual copy).

Options:

Dialect-specific settings:

Additional options are dynamically loaded based on the project’s source language. Run scai code convert --help within a project to see all available options for that dialect.

Common options available across multiple dialects:

Output structure:

snowflake/
  ├── Output/                     Converted Snowflake SQL files
  │   └── <schema>/
  │       └── *.sql
  ├── Reports/
  │   ├── TopLevelCodeUnits.csv   List of all converted objects
  │   ├── Issues.csv              Conversion issues/warnings
  │   └── Summary.html            HTML conversion summary
  └── Logs/                       Conversion log files

Examples:

# Convert using project defaults
scai code convert

# Show all conversion settings for the project's dialect
scai code convert --help

# Convert with custom schema
scai code convert --customschema MY_SCHEMA

# Convert with comments on missing dependencies
scai code convert --comments

# Convert with object renaming file
scai code convert --renamingfile /path/to/renaming.json

# Convert with custom context path
scai code convert --context-path /path/to/context

# Convert only procedures
scai code convert --where "target.objectType = 'procedure'"

scai code deploy¶

Deploy converted SQL code to Snowflake.

scai code deploy [OPTIONS]

Prerequisites:

• Converted code in snowflake/Output/ (from scai code convert).

• Snowflake connection configured (set with scai init -c or project settings).

• Appropriate Snowflake privileges (CREATE TABLE, CREATE VIEW, etc.).

Options:

Behavior notes:

• --warehouse, --schema, and --role temporarily set missing connection fields (in-memory only; the TOML file is not modified).

• If the connection already has a value for an overridden field, an error is returned.

Examples:

# Deploy using default connection
scai code deploy

# Deploy all objects
scai code deploy --all

# Deploy with specific connection
scai code deploy --connection my-snowflake

# Deploy with temporary warehouse override
scai code deploy --warehouse MY_WH

# Deploy filtered objects and their dependencies
scai code deploy --where "target.objectType = 'procedure'" --include-dependencies

scai code find¶

Find code units from the project’s Code Unit Registry.

scai code find [OPTIONS]

Prerequisites:

• A migration project initialized with scai init.

• An initialized Code Unit Registry (generated after scai code convert).

Options:

Output: Table with columns: Id, Fully Qualified Name, Object Type.

Examples:

# Find all code units
scai code find

# Find code units with a specific name
scai code find --where "source.name = 'my_table'"

# Find all code units without limit
scai code find --no-limit

scai code accept¶

Accept the latest converted artifact versions into the snowflake/ output folder.

scai code accept [OPTIONS]

Prerequisites:

• A migration project initialized with scai init.

• Source code must be split and registry files must be generated (run scai code add).

• At least one code conversion run with scai code convert.

Options:

Behavior notes:

• Scans the artifacts/ directory for timestamped conversion outputs.

• For each code unit, selects the most recent version based on the timestamp folder name (yyyyMMdd.HHmmss).

• Copies the latest .sql files into the snowflake/ folder, preserving directory structure.

Examples:

# Accept all latest artifacts
scai code accept

scai code where¶

Show the WHERE clause query reference for code unit filtering.

scai code where

This command displays all queryable fields, supported operators, and usage examples for WHERE clause filtering. It does not require a project directory or network access. The reference is generated at runtime from the Code Unit Registry schema.

Field naming conventions:

• Field names use camelCase with dot-notation: source.objectType, target.objectType, codeStatus.conversion.status, codeStatus.aiVerification.status, codeStatus.registration.status

• Enum values are lowercase: 'table', 'procedure', 'view', 'function', 'completed', 'failed', 'pending', 'excluded'

Commands that support --where:

Examples:

# Show WHERE clause reference
scai code where

scai code resync¶

Re-scan modified converted files and update issue metadata in the Code Unit Registry.

scai code resync

Prerequisites:

• A migration project initialized with scai init.

• Code converted with scai code convert.

Behavior notes:

• Detects code units whose converted files have been modified.

• Re-scans each modified file for SnowConvert issue codes (EWI, FDM, OOS, PRF).

• Updates the issue metadata in the registry.

Examples:

scai code resync

scai ai-convert start¶

Start AI-powered code conversion on converted code.

scai ai-convert start [OPTIONS]

Prerequisites:

• Code converted with scai code convert (generates TopLevelCodeUnits report).

• Snowflake connection configured with snow connection add.

• CREATE MIGRATION privilege granted on the Snowflake account.

• A warehouse configured in the Snowflake connection.

• Must accept AI disclaimers (interactive prompt or -y flag).

Options:

Testing modes:

• Default: Tests converted code on Snowflake only.

• Source system verification: Also runs tests against the source database (requires an instructions file).

Output structure:

ai-converted/
  └── JOB_<timestamp>_<id>/
      ├── fixed/           AI-improved SQL files by object type/schema
      └── tests_sql/       Generated regression tests by database/schema

Examples:

# Start AI code conversion
scai ai-convert start

# Start and wait for completion
scai ai-convert start -w

# Filter with selector (code_conversion_only)
scai ai-convert start --selector my-selector.yml

# Non-interactive (CI/CD)
scai ai-convert start -y -w

# Source system verification
scai ai-convert start -i config/instructions.yml

# Start with temporary warehouse override
scai ai-convert start --warehouse MY_WH

# Convert only tables using WHERE clause
scai ai-convert start --where "target.objectType = 'table'"

scai ai-convert status¶

Check the status of an AI code conversion job.

scai ai-convert status [JOB_ID] [OPTIONS]

Prerequisites:

• A job started with scai ai-convert start.

• Snowflake connection (uses the job’s connection if --connection not specified).

Options:

Examples:

# Check last job status
scai ai-convert status

# Check specific job
scai ai-convert status JOB_20260112041123_XYZ

# Wait and download results
scai ai-convert status -w

# Use different connection
scai ai-convert status -c other-snowflake

scai ai-convert cancel¶

Cancel a running AI code conversion job.

scai ai-convert cancel [JOB_ID] [OPTIONS]

Prerequisites:

• A running job started with scai ai-convert start.

• Snowflake connection (uses the job’s connection if --connection not specified).

Options:

Examples:

# Cancel last job
scai ai-convert cancel

# Cancel specific job
scai ai-convert cancel JOB_20260112041123_XYZ

# Use different connection
scai ai-convert cancel -c other-snowflake

scai ai-convert list¶

List AI code conversion jobs for the current project.

scai ai-convert list [OPTIONS]

Prerequisites:

• A migration project initialized with scai init.

• Snowflake connection for refreshing job status.

Options:

Output: Table with columns: Job ID, Status, Start Time, Duration, Objects. Possible status values: PENDING, IN_PROGRESS, FINISHED, FAILED, CANCELLED.

Examples:

# List recent jobs
scai ai-convert list

# Show all jobs
scai ai-convert list --all

# Refresh with different connection
scai ai-convert list -c other-snowflake

scai ai-convert accept¶

Review, compare, and accept AI-suggested fixes from a completed verification job.

scai ai-convert accept [JOB_ID] [OPTIONS]

Prerequisites:

• A completed AI code conversion job (run scai ai-convert start first).

• If using --selector: a selector file (code_conversion_only). Create with scai object-selector create.

• If using --where: full migration project. Run scai code where for syntax.

Options:

Review modes:

• Summary (--summary, default): Preview affected code units without making changes.

• Interactive (-i): Review each code unit with accept/verify/diff options.

• All (--all): Accept all AI-suggested fixes without prompting.

Interactive actions:

• [d] Diff – open diff tool to compare original and AI-fixed code

• [v] Verify – mark as verified (you applied changes manually)

• [a] Accept – overwrite converted file with AI fix

• [s] Skip – decide later

• [q] Quit – exit (progress is saved)

Examples:

# Interactive review
scai ai-convert accept -i

# Accept all fixes
scai ai-convert accept --all

# Accept from selector
scai ai-convert accept --all -o selector.yml

# Accept filtered by WHERE (full migration)
scai ai-convert accept --all --where "target.objectType = 'table'"

# Preview changes
scai ai-convert accept --summary

# JSON for automation
scai ai-convert accept --summary --json

scai data migrate¶

Migrate data from the source system into a Snowflake account.

scai data migrate [OPTIONS]

Prerequisites:

• Code converted with scai code convert (generates TopLevelCodeUnits report).

• Code deployed with scai code deploy (creates target tables in Snowflake).

• Source database connection configured.

• Snowflake connection configured with INSERT privileges.

• If using --selector: a selector file (code_conversion_only). Create with scai object-selector create.

• If using --where: full migration project; filter tables from Code Unit Registry.

• For Redshift: S3 bucket, Snowflake Storage Integration, and External Stage configured.

Options:

Examples:

# Migrate all tables
scai data migrate --source-connection my-redshift --connection my-snowflake

# Migrate selected tables (selector)
scai data migrate --source-connection my-redshift --connection my-snowflake \
  --selector my-selector.yml

# Migrate filtered by WHERE (full migration)
scai data migrate --source-connection my-redshift --connection my-snowflake \
  --where "source.schema = 'public'"

scai data validate¶

Compare data between source and Snowflake to verify data integrity.

scai data validate [OPTIONS]

Prerequisites:

• Source database connection configured.

• Snowflake connection configured.

• Tables must exist in both source and target databases.

Options:

Output structure:

results/data-validation/run-YYYY-MM-DD-HH-mm-ss/
  ├── *_data_validation_report.csv   Main validation results
  ├── *_data_validation_report.html  HTML report for review
  └── logs/                          Detailed execution logs

Examples:

# Validate all tables from report
scai data validate

# Validate with selector file
scai data validate --selector my-tables.yml

# Validate filtered by WHERE (full migration)
scai data validate --where "source.schema = 'public'"

# With target database
scai data validate --target-database PROD_DB

# With name mappings
scai data validate --db-mapping "sourcedb:TARGETDB" --schema-mapping "dbo:PUBLIC"

# With explicit connections
scai data validate --source-connection my-sqlserver --connection my-snowflake

scai test seed¶

Generate YAML test case files from an execution log of stored procedure calls.

scai test seed --execution-log <EXECUTION_LOG> [--source-connection <SOURCE_CONNECTION>] [--connection <CONNECTION>] [OPTIONS]

Prerequisites:

• A migration project initialized with scai init.

• An execution log file produced by running the original stored procedures.

• Code converted with scai code convert.

Options:

Output: One YAML test case file per procedure at artifacts/<target_db>/<target_schema>/<object_type>/.../<procedure_name>.yml.

Examples:

# Generate test cases
scai test seed --execution-log artifacts/exec_log.csv

# Limit to 5 cases per procedure
scai test seed --execution-log artifacts/exec_log.csv --max-cases 5

# Append to existing test files
scai test seed --execution-log artifacts/new_exec_log.csv --append

scai test capture¶

Capture test baselines from the source database.

scai test capture [--source-connection <SOURCE_CONNECTION>] [--connection <CONNECTION>] [OPTIONS]

Prerequisites:

• A migration project initialized with scai init.

• Test YAML files in artifacts/**/test/*.yml (generated by scai test seed).

• A configured source database connection.

Options:

Output: JSON baseline files written to .scai/baselines/ (or the directory specified by --baseline-dir).

Examples:

# Capture baselines
scai test capture

# With explicit connections
scai test capture --source-connection my-sqlserver --connection my-snowflake

# Custom baseline directory
scai test capture --baseline-dir ./my-baselines

scai test validate¶

Validate Snowflake procedures against captured baselines.

scai test validate [--connection <CONNECTION>] [OPTIONS]

Prerequisites:

• A migration project initialized with scai init.

• Baselines captured with scai test capture.

• A configured Snowflake connection.

Options:

Examples:

# Validate all procedures
scai test validate

# Filter by procedure name
scai test validate --pattern "my_proc.*"

# Create validation schema first
scai test validate --create-schema

# Use local baselines
scai test validate --baseline-dir ./my-baselines

scai object-selector create¶

Create a selector file to filter objects for data migration and other operations.

scai object-selector create [OPTIONS]

Prerequisites:

• Code converted with scai code convert (generates TopLevelCodeUnits report).

Options:

Output: A YAML selector file with the following structure:

objects:
  - code_unit_id: <database>.<schema>.<name>
    type: TABLE | VIEW | PROCEDURE | ...
    source: { database, schema, name }
    target: { database, schema, name }

Examples:

# Create selector file
scai object-selector create

# Create with custom output path
scai object-selector create -o custom-selector.yml

scai license install¶

Install an offline license for running conversions without online activation.

scai license install -p <LICENSE_PATH>

Prerequisites:

• A valid offline license file (.lic) from Snowflake.

Use cases:

• Running in air-gapped environments without internet.

• CI/CD pipelines that cannot use online activation.

• Environments with restricted network access.

Options:

Examples: