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mencoro

Mencoro MCP server

Biggest tracked-query movers

get_query_movers
Read-onlyIdempotent

Ranks tracked queries by metric change between two equal windows to surface top gainers and losers. Use to see which queries improved or dropped versus the prior period.

Instructions

Ranks a project's tracked queries by how much a metric changed between the given window and the immediately preceding window of equal length — the biggest gainers and losers. Each row is one tracked query (a single engine + country) with its current position/share/sentiment and the signed trend delta (positive = improved). Sort by one of the trend keys; sortOrder desc = top gainers, asc = top losers. Dates must fall within the data retention window. Answers questions like "which queries moved the most" or "my biggest gains and drops versus last period".

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
dateToYes
offsetNo
sortByNowhich trend delta to rank bytrend_share_of_voice
enginesNoallowed values: chatgpt, perplexity, google_ai_overview, google_ai_mode, google_serp, google_shopping
dateFromYes
countriesNoISO-3166 alpha-2 country codes (e.g. "US", "GB", "DE"); a project's configured codes are listed by get_available_filters
projectIdYes
sortOrderNodesc for top gainers, asc for top losersdesc
organizationIdYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.1.0

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive), so the bar is lower. The description adds genuinely useful behavior: 'Dates must fall within the data retention window', the per-row structure (one tracked query = single engine + country), and the sign convention (positive = improved), none of which is in the annotations.

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 core function is front-loaded in the first sentence, and each subsequent sentence (row semantics, sort keys, retention constraint, example questions) earns its place. It is slightly dense but not padded or repetitive.

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?

With no output schema, the description usefully describes the return rows (current position/share/sentiment plus signed trend delta) and the retention constraint. For a 10-param tool it is largely complete, though it says nothing about the enum values for sortBy or the engines/countries filters beyond what the schema already carries.

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

Parameters4/5

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

Schema coverage is only 40%, so the description must compensate, and it does for the crucial params: it defines the dateFrom/dateTo window relationship (current vs immediately preceding equal-length window) and the sort semantics ('sortOrder desc = top gainers, asc = top losers'). Pagination (limit/offset) and the ID params are left to the schema, keeping it from a 5.

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 states a precise verb+resource+scope: 'Ranks a project's tracked queries by how much a metric changed between the given window and the immediately preceding window.' This clearly distinguishes it from sibling time-series tools (get_tracked_query_time_series, get_rank_tracking_time_series), which track one query over time rather than ranking movers across queries.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It gives concrete usage context via example questions ('which queries moved the most', 'my biggest gains and drops versus last period'), making the intended scenario obvious. It does not, however, name alternative tools or state explicit exclusions (e.g. when to prefer a time-series tool over this one), so it stops short of a 5.

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