菜单
Validate migrated data between source and Snowflake using cloud validation (SPCS). Setup, run, poll, and end-of-run summary. Triggers: validate data, validate tables, data validation, check data.
用 Codex 或 Claude 帮你安装 复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。
基于 SOC 职业分类
Identify SQL Server migration anti-patterns — performance blockers, architecture/security considerations, and behavioral differences — by running `scai assessment anti-patterns`, which buckets SnowConvert's already-recorded issue codes by priority and writes JSON for the parent assessment multi-report. Use for anti-patterns, performance/architecture concerns in SQL Server → Snowflake migrations;
Analyze SSIS packages from SnowConvert ETL.* outputs and source .dtsx files. Classifies packages, scores migration complexity, and produces JSON for the parent assessment multi-report.
Analyze Informatica Power Center workflows/mappings from SnowConvert ETL.* outputs and source XML files. Classifies workflows, scores migration complexity, and produces JSON for the parent assessment multi-report.
Analyzes workloads to be migrated to Snowflake using SnowConvert assessment reports. Routes to specialized sub-skills for high-quality assessments. Use this skill when user wants to do an assessment of their code or ETL workload, waves generation, object exclusion, anti-patterns, sql dynamic and/or ETL analysis (SSIS)
Set up a migration project — connect to source, initialize, extract objects, convert, and assess. Covers steps 1-5 of the migration lifecycle.
End-to-end database migration to Snowflake. Orchestrates the full migration lifecycle from source connection through initial conversion. Triggers: migrate, migration, migrate to snowflake, end to end migration, e2e migration, full migration.
| name | validate-objects |
| description | Validate migrated data between source and Snowflake using cloud validation (SPCS). Setup, run, poll, and end-of-run summary. Triggers: validate data, validate tables, data validation, check data. |
Tell the user:
Data Validation — I'll compare your migrated data against the source to verify row counts, schema matches, and data integrity.
Call configure() to retrieve the current configuration.
Check the returned values for snowflake_connection, source_connection, and snowflake_database:
configure with the updated values.configure with all of them.Verify a compute_pool is configured (shown in the configure output under "Cloud (SPCS) configured"). If not, ask the user for the compute pool name and call configure(compute_pool="<POOL>").
Load actions/validate_tables.md.
The error-first data validation report (Result + Workflow, Errors, Suggested fixes) is produced in actions/validate_tables.md Step 5 via validate_data_status(). Do not substitute migration_status() for that report.
After validate_tables.md completes (including the summary and teardown offer), optionally call migration_status() for wave-level context only:
configure() call will auto-advance to the next wave.migration_status() shows no remaining waves (all-waves-done), invoke ../data-infrastructure/teardown/SKILL.md unconditionally before returning to the parent — in addition to the per-wave teardown prompt in validate_tables.md Step 6 when applicable.