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Skills/github/awesome-copilot/snowflake-semanticview
snowflake-semanticview logo

snowflake-semanticview

github/awesome-copilot
9K installs35K stars
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Installation

npx skills add https://github.com/github/awesome-copilot --skill snowflake-semanticview

Summary

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 connection setup.

SKILL.md

Snowflake Semantic Views

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 add per 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

  1. Confirm the target database, schema, role, warehouse, and final semantic view name.
  2. Confirm the model follows a star schema (facts with conformed dimensions).
  3. Draft the semantic view DDL using the official syntax:
  • https://docs.snowflake.com/en/sql-reference/sql/create-semantic-view
  1. Populate synonyms and comments for each dimension, fact, and metric:
  • Read Snowflake table/view/column comments first (preferred source):
  • https://docs.snowflake.com/en/sql-reference/sql/comment
  • 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.
  1. 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.
  2. Create a temporary validation name (for example, append __tmp_validate) while keeping the same database and schema.
  3. Always validate by sending the DDL to Snowflake via Snowflake CLI before finalizing:
  • Use snow sql to execute the statement with the configured connection.
  • If flags differ by version, check snow sql --help and use the connection option shown there.
  1. If validation fails, iterate on the DDL and re-run the validation step until it succeeds.
  2. Apply the final DDL (create or alter) using the real semantic view name.
  3. 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;
  1. 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:
  • https://docs.snowflake.com/en/sql-reference/sql/comment
  • 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.

Score

0–100
81/ 100

Grade

B

Popularity23/30

8,796 installs — solid traction. Source repo has 35,018 GitHub stars.

Completeness27/30

Documented: full SKILL.md body, description, one-line install. Missing: category/license metadata.

Trust25/25

Published by github — an official/recognized organization.

Freshness6/15

No update timestamp is tracked for this skill in our catalog.

Scored automatically from popularity, completeness, trust, and freshness — computed only from data in our catalog, never fabricated.

Proud of your score? Add this badge to your README.

Paste a snippet into your GitHub README. The badge updates automatically and links back to this page.

Snowflake Semanticview skill score badge previewScore badge

Markdown

[![Snowflake Semanticview skill](https://www.remoteopenclaw.com/skills/github/awesome-copilot/snowflake-semanticview/badges/score.svg)](https://www.remoteopenclaw.com/skills/github/awesome-copilot/snowflake-semanticview)

HTML

<a href="https://www.remoteopenclaw.com/skills/github/awesome-copilot/snowflake-semanticview"><img src="https://www.remoteopenclaw.com/skills/github/awesome-copilot/snowflake-semanticview/badges/score.svg" alt="Snowflake Semanticview skill"/></a>

Snowflake Semanticview FAQ

How do I install the Snowflake Semanticview skill?

Run “npx skills add https://github.com/github/awesome-copilot --skill snowflake-semanticview” in your terminal. The skill is added to your agent's skills directory and picked up automatically on the next run — no restart or extra configuration needed.

What does the Snowflake Semanticview skill do?

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 connection setup. The full SKILL.md on this page shows the exact instructions the skill gives your agent.

Is the Snowflake Semanticview skill free?

Yes. Snowflake Semanticview is a free, open-source skill published from github/awesome-copilot. As with any third-party skill, review the source repository before installing it into an agent with sensitive access.

Does Snowflake Semanticview work with Claude Code and OpenClaw?

Yes. Skills use the portable SKILL.md format, so Snowflake Semanticview works with Claude Code, OpenClaw, Codex, Hermes, and any other agent that reads SKILL.md skills.

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