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datasets_chrome_extensions_trending

Get trending Chrome Web Store items. Returns stored Chrome Web Store items ranked by the latest observed user and rating-count movement. Filters match the search endpoint; sort is fixed to trending_desc.

Instructions

Get trending Chrome Web Store items. Returns stored Chrome Web Store items ranked by the latest observed user and rating-count movement. Filters match the search endpoint; sort is fixed to trending_desc. Billing: this endpoint costs 1 credit per record returned, with a minimum of 2 (an empty result costs 2, a full page of 100 costs 100).

Input Schema

NameRequiredDescriptionDefault
qNoFull-text query
pageNoPage number
statusNoStatus enum: active, removed
categoryNoExact category
developerNoExact developer
item_typeNoItem type enum: extension, theme, app, unknown
min_usersNoMinimum users
page_sizeNoPage size, max 100
min_ratingNoMinimum rating
permissionNoExact permission
collects_dataNoData-collection filter
developer_emailNoExact developer email
manifest_versionNoManifest version enum: 2, 3
min_rating_countNoMinimum rating count
has_broad_host_accessNoBroad-host-access filter

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed3 schema fields changedv1.17.5
    • addedInput schema / properties / item_type / enum
      Added value: +[
+  "extension",
+  "theme",
+  "app",
+  "unknown"
+]
    • addedInput schema / properties / manifest_version / enum
      Added value: +[
+  2,
+  3
+]
    • addedInput schema / properties / status / enum
      Added value: +[
+  "active",
+  "removed"
+]
  2. Addedv1.5.0

TDQS

A4.4/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does well: it discloses that results are 'stored' items (not live), that ranking is by observed user/rating-count movement, that sort cannot be overridden, and gives precise billing rules (1 credit/record, minimum 2, 100 max). It omits auth requirements and pagination/latency behavior, keeping it just below top marks.

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?

Three sentences, purpose front-loaded, then ranking semantics, then billing. No filler, and the cost detail — while longer — is high-value and clearly delimited.

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?

For a 15-param, no-annotation, no-output-schema tool, the description covers purpose, ranking, filter semantics, fixed sort, and billing, which is most of what an agent needs. It does not describe the returned fields or pagination interplay between page and page_size, leaving a minor gap.

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 description coverage is 100%, so the per-parameter documentation already lives in the schema (baseline 3). The description adds a genuine cross-reference by stating that all filters behave identically to the search endpoint, which meaningfully extends understanding of the 15 params beyond their individual strings.

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?

States a specific verb+resource ('Get trending Chrome Web Store items') and defines the ranking precisely as 'latest observed user and rating-count movement.' It also distinguishes itself from the sibling search endpoint by noting filters match search while sort is fixed to `trending_desc`, so an agent can tell them apart without opening a schema.

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 line 'Filters match the search endpoint; sort is fixed to `trending_desc`' gives clear context for when this tool is the right choice versus the general search endpoint. It stops short of an explicit when-not-to-use or naming a specific alternative, so it is strong but not fully prescriptive.

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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