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ncejda-g2

Snowflake MCP Server

by ncejda-g2

validate_query_without_execution

Generate and validate any SQL query (SELECT, INSERT, UPDATE, DELETE) without execution. Review table references, improvement hints, and execution readiness for safe manual verification.

Instructions

Generate and validate a SQL query without executing it.

This tool can generate ANY type of SQL query including both read and write operations
(SELECT, INSERT, UPDATE, DELETE, etc.) but does NOT execute them. Useful for generating
queries that users want to review and execute elsewhere after manual verification.

IMPORTANT: Write queries (INSERT, UPDATE, DELETE, etc.) can be generated here but
CANNOT be executed through the execute_query tool for safety reasons. Users must
execute write queries directly in Snowflake after manual review.

Parameters:
- sql: SQL query to generate (read or write operations allowed)
- database: Optional database context
- schema: Optional schema context

The tool will:
- Accept both read and write queries
- Check query type (SELECT, INSERT, UPDATE, DELETE, etc.)
- Extract table references
- Provide hints for improvement
- Return the formatted query ready for manual review
- Indicate whether the query can be executed via execute_query (read-only) or not (write)

Examples:
- validate_query_without_execution("SELECT * FROM customers")
- validate_query_without_execution("INSERT INTO orders (id, amount) VALUES (1, 100.00)")
- validate_query_without_execution("UPDATE customers SET status = 'active' WHERE id = 123")
- validate_query_without_execution("DELETE FROM temp_data WHERE created < '2024-01-01'")

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sqlYes
databaseNo
schemaNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description fully discloses behavioral traits: it does not execute queries, it checks query type, extracts table references, provides improvement hints, and indicates executability via execute_query. Since no annotations are present, the description carries the full burden, which it meets comprehensively.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-organized with sections for parameters, behavior, and examples. It is front-loaded with the main purpose and limitation. However, it is slightly verbose (e.g., repeating examples for each query type), and minor trimming could improve conciseness.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (generating any SQL type) and the absence of descriptions in the input schema, the description covers all necessary aspects: behavior, parameter meanings, limitations, and return indications. An output schema exists, so the description appropriately focuses on input and process.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 0% description coverage, but the description adds rich semantics for each parameter: explains 'sql' accepts both read and write operations, 'database' and 'schema' are optional contexts. This significantly adds meaning beyond the schema field names.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool generates and validates SQL queries without execution. It explicitly distinguishes from execute_query by noting that write queries can only be generated here, not executed. The verb 'validate' and resource 'SQL query' are specific, and examples cover all query types.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides explicit when-to-use guidance: for generating queries that users want to review and execute elsewhere. It includes critical exclusions, stating that write queries (INSERT, UPDATE, DELETE) cannot be executed through execute_query, and directs users to execute them in Snowflake after manual review.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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