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Glama

steam_get_store_details

Fetch live Steam store details for a game by AppID or name, including regional pricing, platforms, genres, release date, and developer info.

Instructions

Full store listing for a game, fetched live from Steam: price (per region via cc), platforms, genres, categories, DLC count, developers/publishers, release date, metacritic score, and short description. Use for pricing and store-metadata questions.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
ccNoISO country code for regional pricing.us
appYesAppID (e.g. "730") or exact game name. Prefer an AppID from steam_search_apps for ambiguous names.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYes
appidYes
priceNo
genresNo
is_freeYes
dlc_countNo
platformsYes
categoriesNo
developersNo
metacriticNo
publishersNo
release_dateNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

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 full behavioral burden, and 'fetched live from Steam' usefully signals freshness and an external network call. It says nothing about failure behavior for unknown apps, rate limits, or latency, leaving meaningful gaps for a no-annotation tool.

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?

Two sentences, front-loaded with the resource and its field list, then the usage cue. The field enumeration is dense but each item earns its place by telling the agent what metadata is retrievable.

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?

An output schema exists, so return-value explanation is not required, and the field list plus the `cc` regional-pricing note cover the calling surface adequately. The only shortfall is behavioral detail (error handling, live-fetch cost/latency) that the absent annotations leave unaddressed.

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 both parameters are already documented ('cc' as ISO country code for regional pricing, 'app' as AppID or exact name with a preference for steam_search_apps results). The description's 'price (per region via `cc`)' only reinforces what the schema already states, adding no new syntax or format detail; baseline 3 applies.

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 verb+resource ('Full store listing for a game, fetched live from Steam') and enumerates the payload fields, which makes the tool's scope clear. It does not explicitly distinguish itself from the sibling steam_get_app_overview, which could plausibly overlap on store metadata, so it stops short of a 5.

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?

'Use for pricing and store-metadata questions' gives a clear, concrete usage cue tied to the tool's distinguishing feature (regional pricing). It names no alternatives and no when-not conditions, e.g. directing review or news questions to steam_get_app_reviews / steam_get_game_news, so no exclusion guidance is present.

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