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B2A Fulfillment Factory

B2A Fulfillment Factory

by ceadigital

gcp_catalog_search

Read-only

Search Google Cloud, Vertex AI, Billing SKUs, and A2A service records by keyword to locate relevant catalog entries and return limited results.

Instructions

Sub-millisecond FTS5 search across 17,671 Google Cloud, Vertex AI, Billing SKUs, and A2A service records.

Input Schema

NameRequiredDescriptionDefault
limitNoMax results to return (default 10)
queryYesFTS5 search term (e.g. 'compute engine', 'vertex rag')

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

B3.3/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false, and openWorldHint=true, so the safety profile is covered. The description adds genuine context beyond that: the corpus size and the four record types searched, plus a performance claim. It does not mention result ordering, truncation, or what a hit contains, so it stops short of rich behavioral disclosure.

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 with the core capability first and the corpus scope second. No filler, no restatement of the tool name, and nothing that could be trimmed without losing meaning.

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

Completeness3/5

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

For a two-parameter read-only search this is close to sufficient, and the schema covers all parameters. However, with no output schema, the description offers no hint about result shape, ranking, or whether the sub-millisecond claim implies a hard result cap, leaving the agent to discover return behavior by calling it.

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%, with both 'query' (with FTS5 example terms) and 'limit' (default 10) documented in the schema itself. The description adds nothing about query syntax, match behavior, or ranking, so baseline 3 is appropriate.

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 (search) and resource (Google Cloud, Vertex AI, Billing SKUs, A2A service records) and even quantifies the corpus at 17,671 records. It is clearly distinguishable from generic siblings like vault_knowledge_search by domain, though it never names or contrasts an alternative explicitly.

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?

There is no when-to-use guidance, no exclusions, and no routing to sibling tools such as vault_knowledge_search. An agent must infer that this is the right choice only from the domain nouns in the sentence.

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