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steam_items

Resolve Steam app IDs into store items with weighted community tags, review scores, developer credits, and pricing. Batch enrich up to 100 apps per call using Steam's public API without credentials.

Instructions

Resolve a batch of app ids to store items with weighted tags. Resolves up to 100 Steam app ids in one call to normalized store items via Steam's keyless IStoreBrowseService, each carrying its WEIGHTED community tags, review-score breakdown, developer/publisher credits, release date, platforms and price. The batch enrichment primitive for the community-tag taxonomy. Credential-free public Steam store query API.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
lNoSteam store language name
ccNoStore country code (ISO, selects currency)
appidsYesComma-separated numeric app ids (max 100)
Behavior3/5

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

With no annotations, the disclosure that the tool is 'credential-free', uses Steam's keyless API, and resolves up to 100 app IDs provides useful behavioral context. However, it omits potential rate limits, error handling, or return structure details, which would enhance transparency for a batch tool.

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?

The description is concise (3 sentences) and front-loaded with the core action and key outputs. Every sentence adds value, and the technical terms are explained clearly. There is no verbosity or redundancy.

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?

Given the absence of an output schema, the description compensates by listing returned fields (weighted tags, review score, credits, release date, platforms, price) and noting the API source and batch limit. It lacks only explicit output format details but is otherwise complete for the tool's purpose.

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 coverage is 100%, so the baseline is 3. The description reinforces the max 100 app IDs and mentions 'normalized store items' but does not add significant meaning beyond the schema parameter descriptions. No new constraints or formatting details are introduced.

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 clearly states the tool resolves a batch of app IDs to store items with weighted tags, listing specific returned fields and emphasizing its role as a 'batch enrichment primitive for the community-tag taxonomy'. This effectively communicates the tool's unique value and distinguishes it from sibling Steam tools.

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 for batch enrichment with community tags but does not explicitly state when to use this tool versus alternatives (e.g., steam_app for single app details). No exclusion criteria or alternative recommendations are provided, leaving some ambiguity for the agent.

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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