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semrush-ai-mcp

Question Keywords

semrush_keyword_questions

Find question-based keywords (who, what, where, when, why, how) containing a phrase to build FAQ sections and target People Also Ask and featured snippets.

Instructions

Question-based keywords (who/what/where/when/why/how) containing the phrase — perfect for FAQ sections, featured snippets and People Also Ask targeting.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum number of rows to return (default 10). More rows = more API units.
phraseYes
databaseNoRegional database code, e.g. us, uk, de, fr, es, it, br, au, ca, in (default: us)us

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

C2.9/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full behavioral burden, and it discloses almost nothing beyond the keyword type. It omits cost/API-unit implications (hinted at only in the schema's limit field), pagination, and return shape — all relevant for a query tool with no output schema.

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?

One tightly written sentence, front-loading the resource and its qualifier before the benefit clause. Nothing is wasted, though the marketing-flavored tail ('perfect for...') spends words on things other than invocation guidance.

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 simple read-only keyword query with no annotations and no output schema, the description is minimally adequate but leaves gaps: no phrase-matching semantics, no note that higher limit values consume more API units, and no indication of the returned data structure. It is enough to call the tool, not enough to call it well.

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 67%: limit and database are documented in-schema, while the required 'phrase' parameter has no description in either place. The description adds no parameter meaning (format, matching behavior, regional scoping) beyond what the schema already supplies, 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 resource — question-based keywords matching a phrase — and defines the qualifying pattern (who/what/where/when/why/how). This meaningfully distinguishes it from sibling semrush_related_keywords, though it never names that sibling 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?

The sentence describes downstream applications of the results (FAQ sections, featured snippets, People Also Ask) rather than when to choose this tool over siblings like semrush_related_keywords or semrush_keyword_overview. No conditions, prerequisites, or alternatives are given for tool selection.

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