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Debanjan29

mcp-sqlserver

by Debanjan29

export_query

Execute SQL SELECT queries and export results as CSV or JSON for easy data retrieval.

Instructions

Execute a SELECT query and return results as CSV or JSON format

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sqlYesThe SQL SELECT query
formatYesOutput format: csv or json
serverNoTarget server name (uses default if omitted)
databaseNoDatabase name (uses connection default if omitted)
Behavior3/5

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

With no annotations, the description carries the full burden. It states the query type (SELECT) which implies a read-only operation, but it does not disclose any other behaviors such as output size limits, server connection handling, or error behavior. The description is minimal but not misleading; it gives the core behavior without added nuance.

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

Conciseness5/5

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

The description is a single, clear sentence with no redundant words or filler. It states the action and the key output types upfront, making it efficient and easy to scan.

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

Completeness2/5

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

Given the tool has 4 parameters, no annotations, and no output schema, the description is too sparse. It does not clarify how this tool relates to execute_query, what the exact structure of the returned CSV/JSON is, or any constraints (e.g., row limits, transaction behavior). An agent would lack key information needed to call it correctly and interpret results.

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

Parameters3/5

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

Schema description coverage is 100%, so all parameters are documented in the schema. The description does not add extra meaning beyond the schema; it essentially restates the format parameter. Since the schema already defines each parameter clearly, the description adds no additional semantic value.

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

Purpose4/5

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

The description clearly states the tool executes a SELECT query and returns results in CSV or JSON format. The verb 'execute' and resource 'query' are specific, and the format mention distinguishes it from raw query execution. However, it does not explicitly differentiate from sibling execute_query, so it's clear on what it does but not why it's distinct.

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

Usage Guidelines2/5

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

No guidance is provided on when to use this tool versus alternatives like execute_query. It does not state that this tool is preferred when format conversion is needed or that execute_query returns default format. The description only describes the action without context for selection.

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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