Snowflake Semantic Views
SkillDatabases & dataLets your agent create, edit, and validate Snowflake semantic views using the Snowflake CLI.
Instructions available. Your AI can read the instructions. Execution depends on the setup they require.
Account requirements not reviewed. Check the skill instructions before use; ahel provides instructions and does not run this skill.
Add ahel to your AI once: Claude, ChatGPT, Cursor, Claude Code or Codex. Then ask it to use this.
Then ask your AI: use the Snowflake Semantic Views skill
About this skill
Create, alter, and validate Snowflake semantic views using Snowflake CLI (snow). Use when asked to build or troubleshoot semantic views/semantic layer definitions with CREATE/ALTER SEMANTIC VIEW, to validate semantic-view DDL against Snowflake via CLI, or to guide Snowflake CLI installation and conn
What this skill tells your AI
The instructions your AI receives, as published by github/awesome-copilot in skills/snowflake-semanticview/SKILL.md and read by ahel’s review.
One-Time Setup
- Verify Snowflake CLI installation by opening a new terminal and running
snow --help. - If Snowflake CLI is missing or the user cannot install it, direct them to https://docs.snowflake.com/en/developer-guide/snowflake-cli/installation/installation.
- Configure a Snowflake connection with
snow connection addper https://docs.snowflake.com/en/developer-guide/snowflake-cli/connecting/configure-connections#add-a-connection. - Use the configured connection for all validation and execution steps.
Workflow For Each Semantic View Request
- Confirm the target database, schema, role, warehouse, and final semantic view name.
- Confirm the model follows a star schema (facts with conformed dimensions).
- Draft the semantic view DDL using the official syntax:
- Populate synonyms and comments for each dimension, fact, and metric:
- Read Snowflake table/view/column comments first (preferred source):
- If comments or synonyms are missing, ask whether you can create them, whether the user wants to provide text, or whether you should draft suggestions for approval.
- Use SELECT statements with DISTINCT and LIMIT (maximum 1000 rows) to discover relationships between fact and dimension tables, identify column data types, and create more meaningful comments and synonyms for columns.
- Create a temporary validation name (for example, append
__tmp_validate) while keeping the same database and schema. - Always validate by sending the DDL to Snowflake via Snowflake CLI before finalizing:
- Use
snow sqlto execute the statement with the configured connection. - If flags differ by version, check
snow sql --helpand use the connection option shown there.
- Use
- If validation fails, iterate on the DDL and re-run the validation step until it succeeds.
- Apply the final DDL (create or alter) using the real semantic view name.
- Run a sample query against the final semantic view to confirm it works as expected. It has a different SQL syntax as can be seen here: https://docs.snowflake.com/en/user-guide/views-semantic/querying#querying-a-semantic-view Example:
SELECT * FROM SEMANTIC_VIEW(
my_semview_name
DIMENSIONS customer.customer_market_segment
METRICS orders.order_average_value
)
ORDER BY customer_market_segment;
- Clean up any temporary semantic view created during validation.
Synonyms And Comments (Required)
- Use the semantic view syntax for synonyms and comments:
WITH SYNONYMS [ = ] ( 'synonym' [ , ... ] )
COMMENT = 'comment_about_dim_fact_or_metric'
- Treat synonyms as informational only; do not use them to reference dimensions, facts, or metrics elsewhere.
- Use Snowflake comments as the preferred and first source for synonyms and comments:
- If Snowflake comments are missing, ask whether you can create them, whether the user wants to provide text, or whether you should draft suggestions for approval.
- Do not invent synonyms or comments without user approval.
Validation Pattern (Required)
- Never skip validation. Always execute the DDL against Snowflake with Snowflake CLI before presenting it as final.
- Prefer a temporary name for validation to avoid clobbering the real view.
Example CLI Validation (Template)
# Replace placeholders with real values.
snow sql -q "<CREATE OR ALTER SEMANTIC VIEW ...>" --connection <connection_name>
If the CLI uses a different connection flag in your version, run:
snow sql --help
Notes
- Treat installation and connection setup as one-time steps, but confirm they are done before the first validation.
- Keep the final semantic view definition identical to the validated temporary definition except for the name.
- Do not omit synonyms or comments; consider them required for completeness even if optional in syntax.
Signals
- GitHub stars
- 40k
- Forks
- 5k
- Last commit
- Oct 2026
Advanced
- Item type
- skill
- Key
snowflake-semanticview- Source
- github.com/github/awesome-copilot
github.com/github/awesome-copilot
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