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JavaScript
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datasets_playstation_games_facets

Returns facet counts for PlayStation games, letting you filter and analyze titles by publisher, genre, platform, price tier, and more.

Instructions

Facet PlayStation games dataset. Returns terms aggregation counts for the PlayStation games dataset. Facet enum: publisher, classification, genres, platforms, content_rating_authority, content_descriptors, price_tier, service_branding, region, release_year, run_id, is_free, is_addon, is_tied_to_subscription, coming_soon. price_tier enum: free, under_5, 5_to_10, 10_to_20, 20_to_40, 40_to_60, 60_plus.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
qNoFull-text query over name and publisher, max 256 characters
facetYesFacet enum: publisher, classification, genres, platforms, content_rating_authority, content_descriptors, price_tier, service_branding, region, release_year, run_id, is_free, is_addon, is_tied_to_subscription, coming_soon
genreNoExact genre filter, max 128 characters
regionNoExact store region (country code) filter, max 128 characters
run_idNoExact crawl run-id filter, max 128 characters
is_freeNoFilter by free flag
on_saleNoFilter by titles currently discounted (discount_pct > 0)
brandingNoExact subscription/service-branding filter, max 128 characters
is_addonNoFilter add-ons vs games
platformNoExact platform filter: PS4 or PS5
publisherNoExact publisher filter, max 128 characters
concept_idNoExact concept id filter, max 128 characters
price_tierNoPrice-tier enum: free, under_5, 5_to_10, 10_to_20, 20_to_40, 40_to_60, 60_plus
coming_soonNoFilter for pre-release titles
np_title_idNoExact np_title_id filter, max 128 characters
classificationNoExact classification filter, max 128 characters
content_ratingNoExact content-rating authority filter, max 128 characters
min_star_countNoMinimum number of star ratings
max_price_valueNoMaximum current price in minor units
min_price_valueNoMinimum current price in minor units
min_star_ratingNoMinimum average star rating, 0 through 5
max_release_yearNoMaximum release year
min_discount_pctNoMinimum discount percent, 0 through 100
min_release_yearNoMinimum release year
content_descriptorNoExact content-descriptor filter, max 128 characters
is_tied_to_subscriptionNoFilter subscription-included titles

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changedv1.17.5
    • addedInput schema / properties / facet / enum
      Added value: +[
+  "publisher",
+  "classification",
+  "genres",
+  "platforms",
+  "content_rating_authority",
+  "content_descriptors",
+  "price_tier",
+  "service_branding",
+  "region",
+  "release_year",
+  "run_id",
+  "is_free",
+  "is_addon",
+  "is_tied_to_subscription",
+  "coming_soon"
+]
    • addedInput schema / properties / price_tier / enum
      Added value: +[
+  "free",
+  "under_5",
+  "5_to_10",
+  "10_to_20",
+  "20_to_40",
+  "40_to_60",
+  "60_plus"
+]
  2. Changed1 schema field changed
    • changedInput schema / properties / facet / description
      Previous value: -"Facet enum: publisher, classification, genres, platforms, content_rating_authority, price_tier, service_branding, region, release_year, run_id, is_free, is_addon, coming_soon"New value: +"Facet enum: publisher, classification, genres, platforms, content_rating_authority, content_descriptors, price_tier, service_branding, region, release_year, run_id, is_free, is_addon, is_tied_to_subscription, coming_soon"
  3. Addedv1.5.0

TDQS

A3.6/5.0
Behavior3/5

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

With no annotations, the description must carry the behavioral burden. It clearly discloses a read-only aggregation behavior and lists the facet enums, but it does not explain how optional filters affect the aggregation, whether bucket limits apply, or what the response structure looks like. These are moderate gaps, especially given the absence of an 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?

The description is front-loaded with the purpose, but the first two sentences redundantly mention 'PlayStation games dataset'. The long enum lists are helpful at a glance yet duplicate the schema. Overall, it is reasonably concise and well-structured, with only minor redundancy.

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?

The tool has 26 parameters and no output schema, so the description should clarify the return format and how filters combine with the facet aggregation. It only says 'terms aggregation counts' without detailing the response structure or filter interaction. Despite full schema documentation of parameters, the agent is left guessing about output specifics, making the description partially complete.

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%, so the schema already documents all 26 parameters, including the required `facet` and every filter. The description redundantly repeats the facet and price_tier enums, adding no new meaning beyond the schema. It does not describe parameter interactions, formatting, or other semantics, so the baseline of 3 is appropriate.

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 specific behavior ('Returns terms aggregation counts') and identifies the resource ('PlayStation games dataset'). This distinctively differentiates it from sibling tools like `datasets_playstation_games_item` (single record) and `datasets_playstation_games_search` (search results), so an agent can tell them apart without opening the schema.

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 via the term 'facet' and the aggregation-counts behavior, but it provides no explicit when-to-use guidance, exclusions, or mentions of alternatives. It does not tell the agent to prefer this tool for distribution summaries and `datasets_playstation_games_search` for actual records, so usage is left to inference.

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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