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List Trending Themes

list_trending_themes
Read-onlyIdempotent

List themes that are currently heating up (sorted by trend change %), to catch demand that is growing. A theme is the "market-signal layer": it aggregates multiple opportunities and carries 30-day mentions, trend direction and audience clarity. (Pro tool)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoNumber of themes to return, 1-30. Default 15.
min_mentionsNoMinimum 30-day discussion count, filters out noise. Default 2.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changed
    • addedInput schema / properties / limit / description
      Added value: +"Number of themes to return, 1-30. Default 15."
    • addedInput schema / properties / min_mentions / description
      Added value: +"Minimum 30-day discussion count, filters out noise. Default 2."
  2. First observed

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, and non-destructive behavior. The description adds valuable behavioral context: sorting by trend change %, aggregating multiple opportunities, and the data fields carried (30-day mentions, trend direction, audience clarity). It also notes 'Pro tool' access. No contradictions with annotations.

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 sentences, no fluff. The main action and purpose are front-loaded in the first sentence, and the second sentence concisely defines the domain concept. Every word earns its place.

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

Completeness5/5

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

For a simple list tool with 2 parameters, full schema coverage, and an output schema present, the description fully covers the tool's purpose, sorting behavior, data content, and use case. Nothing critical is missing.

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 limit and min_mentions fully documented in the schema. The description text adds no parameter-specific details beyond the schema, so it just meets the baseline without enhancing understanding.

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 uses a specific verb ('List') and resource ('themes'), further scoped by 'currently heating up' and a concrete sort order ('trend change %'). It clearly distinguishes this tool from siblings like get_theme by describing the theme concept and trending focus.

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?

The description explicitly states the intended use case ('to catch demand that is growing'), providing clear context for when this tool is appropriate. However, it does not explicitly mention when not to use it or name alternative tools (e.g., get_theme), so it stops short of full alternatives guidance.

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

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