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Check Steam Wishlist Updates

steam_check_wishlist_updates

Detect wishlist updates by comparing current data with a local snapshot, including releases, demos, date changes, additions, removals, and news signals.

Instructions

Compare the current wishlist with a local snapshot for releases, demos, date changes, additions, removals, and playtest/beta/demo news signals.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
steamidNo
sinceDaysNo
maxNewsAppsNo
saveSnapshotNo
maxMetadataAppsNo
includeNewsSignalsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataYes
summaryYes
Behavior2/5

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

No annotations are provided, so the description carries the full burden of disclosing behavioral traits. It mentions comparison with a 'local snapshot', implying stateful behavior and potential side effects (e.g., saving snapshots), but does not explain whether the tool itself saves snapshots, how it interacts with local storage, or any rate limits/permissions needed. The description is insufficient to understand the tool's side effects.

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 a single sentence that front-loads the core purpose ('Compare the current wishlist with a local snapshot') and lists the detected items. It is relatively concise but slightly long. It could be improved by breaking into two sentences or adding structure, but overall it is efficient.

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

Completeness2/5

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

Given the tool has 6 parameters, no annotations, and an output schema (but not shown), the description is incomplete. It lacks parameter explanations, usage context, and behavioral details. For a tool that involves snapshots and comparisons, the minimal description leaves significant gaps for an AI agent to use it correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters1/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 6 parameters with 0% description coverage, meaning no properties have descriptions in the schema. The tool description completely fails to explain any of these parameters (steamid, sinceDays, maxNewsApps, saveSnapshot, maxMetadataApps, includeNewsSignals). An AI agent would have no way to understand what each parameter does or how to use them correctly.

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 that the tool compares the current Steam wishlist with a local snapshot to detect various types of updates (releases, demos, date changes, additions, removals, news signals). It uses a specific verb ('Compare') and resource ('wishlist with a local snapshot'), and the listed update types distinguish it from sibling tools like steam_get_wishlist which only retrieves the wishlist without comparison.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no explicit guidance on when to use this tool versus alternatives. It does not mention prerequisites (like taking a snapshot), nor does it contrast with related tools such as steam_get_wishlist or steam_update_center. The usage context is only implied through the description of what the tool does.

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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