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Sanjeev4523

metabase-lite-mcp

by Sanjeev4523

run_query_preview

Execute a read-only query preview to fetch results, validating that the query is read-only before running it.

Instructions

Execute a read-only query preview and return results. Validates queries are read-only before execution.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
parametersNoQuery parameters
constraintsNoResult constraints
output_fileYesFile path where full JSON results will be written
dataset_queryYesMetabase dataset_query object
Behavior3/5

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

No annotations are provided, so the description bears full responsibility for disclosing behavior. It does state the tool is read-only and that it 'Validates queries are read-only before execution,' which adds safety context. However, it does not clarify whether the function returns preview rows directly, whether it overwrites 'output_file', or any error/limit behaviors. The file-writing side effect is only briefly hinted at via the schema's 'output_file' description.

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 two sentences, direct, and front-loaded with the main action. Every word adds value: it names the operation, the resource, the read-only guarantee, and the validation step. No filler or redundancy.

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 no output schema and no annotations, the description should clarify the return value and side effects. It says 'return results' and that 'full JSON results will be written' to output_file, but it does not explain what the function actually returns (e.g., a preview subset, a status code) or whether output_file is overwritten. The nested dataset_query structure and constraints are well-documented in the schema, but the tool's runtime behavior remains ambiguous.

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 (dataset_query, output_file, parameters, constraints) already have descriptive text in the schema. The description adds no additional param-level meaning beyond the overall 'read-only' intent. This meets the baseline for full schema coverage with no extra value from the description.

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's function: 'Execute a read-only query preview and return results.' It uses a specific verb ('execute'), identifies the resource ('query preview'), and adds the key characteristic of read-only with validation. This distinguishes it from sibling tools that cover CRUD operations on cards/dashboards, none of which execute queries.

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

Usage Guidelines3/5

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

The usage context is implied by 'read-only query preview' and the error-checking behavior ('Validates queries are read-only before execution'). However, the description does not explicitly state when to use this tool versus alternatives, nor does it mention any siblings or exclusions. Since there is no sibling that also runs queries, the purpose is reasonably clear, but explicit guidance is missing.

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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