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@qybbs/custom-bigquery-mcp

@qybbs/custom-bigquery-mcp

by qybbs
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Remote

describe_table

Retrieve detailed schema, column descriptions, and partitioning information for an allowed BigQuery table.

Instructions

Get detailed schema, column descriptions, and partitioning information for an allowed BigQuery table.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "datasetId": "<datasetId>",
      "tableId": "<tableId>"
    },
    "name": "describe_table"
  }
}

Input Schema

NameRequiredDescriptionDefault
tableIdYesBigQuery table ID
datasetIdYesBigQuery dataset ID

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

B3.4/5.0
Behavior3/5

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

No annotations are provided, so the description carries the burden, and it does disclose the returned content (schema, column descriptions, partitioning) and that the table must be an 'allowed' one, implying access control. However, it doesn't state that the operation is read-only, what happens for a missing or forbidden table, or any limits. Partial disclosure without annotations warrants a 3.

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?

A single front-loaded sentence that names the action, the returned artifacts, and the resource scope with no filler. Every clause earns its place.

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

Completeness4/5

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

For a simple two-parameter read tool with no output schema and no annotations, the description covers the purpose and the shape of the returned data well. It could go further on error/permission behavior, but nothing essential for correct invocation is missing.

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 coverage is 100% with both required parameters (datasetId, tableId) fully documented in the schema. The description adds no additional meaning about parameter format or constraints, so the baseline of 3 applies.

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?

States a specific verb (Get) and resource (schema, column descriptions, partitioning information for a BigQuery table), which is clearly distinct from the list/search/execute/estimate siblings. It doesn't explicitly name a sibling to contrast with, so it lands at 4 rather than 5.

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?

The description gives no when-to-use guidance, no indication of when to prefer this over list_allowed_tables or search_allowed_tables, and no prerequisites. The only contextual hint is the word 'allowed', which implies an access constraint but doesn't tell the agent when to reach for this tool.

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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