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phalkmin

trendzeist-mcp

mine_questions

Mines long-tail questions from Google Autocomplete for a seed keyword, de-duplicates and tags them with title angles to fuel FAQ sections and answer-engine content.

Instructions

Long-tail questions people type about a seed, from Google Autocomplete ('how to', 'why', 'what is', 'vs' ... expansions), de-duplicated and tagged with a title angle. Feeds FAQ sections and answer-engine (AEO) content. Up to ~16 throttled requests per call; results cached 24 h. limit: 1-100.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
geoNo
seedYes
limitNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.3.0

TDQS

A3.7/5.0
Behavior4/5

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

Since no annotations are provided, the description carries the full burden of behavioral disclosure. It mentions throttling (up to ~16 requests per call), 24-hour caching, de-duplication, and tagging with a title angle. These are concrete behaviors that help the agent understand side effects and constraints. It does not mention read-only nature, but that is implied by the operation. The coverage is strong for a read-only mining tool.

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

Conciseness4/5

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

The description is a single, dense sentence that packs purpose, examples, behavioral details, and limit into a compact form. It is front-loaded with the core purpose. While it could be split for readability, every clause adds useful information, and it avoids redundancy. It is appropriately concise for the amount of detail.

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?

An output schema exists, so return values are covered. However, the description lacks parameter semantics and explicit usage guidance. It does not explain how 'seed' and 'geo' affect results, nor does it mention any ordering or filtering behavior. The behavioral details (throttling, caching) are good, but the missing parameter explanations and sibling differentiation make the tool incomplete for an agent to call it correctly without additional context.

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

Parameters2/5

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

Schema description coverage is 0%, so the description must compensate for parameter explanations. It only mentions 'limit: 1-100' in the description, providing a range for that parameter. However, it does not explain what 'seed' refers to (beyond being a starting topic) nor the meaning or possible values of 'geo'. With three parameters and 0% schema coverage, this is a significant gap that leaves the agent guessing about required input semantics.

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 mines long-tail questions from Google Autocomplete for a given seed, with explicit examples of expansions ('how to', 'why', 'what is', 'vs'). It distinguishes itself from siblings like related_queries or suggest_keywords by focusing on question-form queries and mentions the downstream use (FAQ, AEO content). The verb 'mine' plus resource 'questions' is specific and unambiguous.

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 description implies usage by mentioning 'Feeds FAQ sections and answer-engine (AEO) content', which tells the agent when this tool is relevant. However, it does not explicitly contrast with sibling tools (e.g., related_queries, suggest_keywords) or state when not to use it. The context is present but not explicit, so the agent must infer the distinction.

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