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qybbs

@qybbs/custom-bigquery-mcp

search_allowed_tables

Find permitted BigQuery tables and their schemas by keyword, returning table descriptions, partitioning, clustering, and field details in one call.

Instructions

Search allowed tables and their schemas by a keyword (e.g., 'transaction', 'customer'). Returns table description, partitioning columns, clustering columns, and field schemas in one call.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
keywordYesThe search keyword to filter table names and datasets

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A3.6/5.0
Behavior3/5

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

With no annotations, the description carries the full behavioral burden. It does disclose the return payload (table description, partitioning columns, clustering columns, field schemas), which is useful since no output schema exists, but it says nothing about read-only semantics, result limits, pagination, or match scope (names vs. field names).

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?

Two tight sentences: the action and its scope are front-loaded, and the return contents are summarized in a single clause with no filler.

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?

Given one parameter, no annotations, and no output schema, the description covers everything essential: what is searched, what the keyword does, and what is returned. Minor gaps remain around result limits and whether matching spans field names, but nothing blocks correct invocation.

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%, and the single 'keyword' parameter is already documented there, so the baseline is 3. The description adds only example keywords, which gives a marginal sense of expected input but no format, matching rules, or case-sensitivity detail.

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 and resource ('Search allowed tables and their schemas by a keyword') and names what comes back. It implies but never explicitly names how it differs from the sibling list_allowed_tables, so an agent must infer the keyword-vs-enumerate distinction.

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 keyword examples ('transaction', 'customer') imply the intended usage context, but there is no explicit when-to-use/when-not guidance and no routing to list_allowed_tables or describe_table for narrowing or expanding results.

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