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Wishlist activity over time

get_wishlist_activity
Read-onlyIdempotent

Wishlist adds, deletes, purchases and gifts for one game, grouped by day, week (Monday start) or month, with the number of outstanding wishlists at the end of each period. Optional single-country filter. Days are GMT, as Valve reports them.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "appid": "<appid>"
    },
    "name": "get_wishlist_activity"
  }
}

Input Schema

NameRequiredDescriptionDefault
appidYesSteam app id, from list_games
countryNoTwo-letter country code, e.g. US, DE, CN
end_dateNoLast day, YYYY-MM-DD. Default: the newest day with data (yesterday)
group_byNoday, week, month or totalweek
start_dateNoFirst day, YYYY-MM-DD. Default: 28 days before end_date

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.7/5.0
Behavior3/5

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

Annotations already declare this a read-only, idempotent, non-destructive, closed-world operation, so the safety profile is covered. The description adds genuinely useful behavioral detail the annotations lack: days are GMT as Valve reports them, weeks start Monday, and outstanding wishlists are reported at period end. That is real added context, though nothing is said about data freshness limits or row-volume behavior for long ranges.

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 compact sentences, front-loaded with what is returned, then grouping, then the country filter and timezone caveat. Every clause carries information an agent cannot get from the schema, and nothing is redundant.

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?

With no output schema, the description does the work of describing the return shape (per-period counts plus end-of-period outstanding totals), which is the key thing an agent needs. Defaults are handled by the schema, so their absence here is fine. The unmentioned 'total' grouping option is the only substantive hole.

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 coverage is 100%, so the baseline is 3, but the description adds meaning the schema does not carry: the Monday week start and the GMT day boundary directly affect how start_date/end_date and group_by behave. It also clarifies that country filtering is optional and single-valued. Minor gap: group_by's 'total' option in the schema enum is never mentioned in the description.

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?

Names a specific resource (wishlist adds, deletes, purchases, gifts for one game) plus the grouping and the outstanding-count metric, so an agent knows exactly what data comes back. It does not explicitly differentiate itself from siblings like get_wishlist_breakdown or get_wishlist_conversion, leaving the time-series framing to imply the distinction.

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?

Usage is only implied: the day/week/month grouping signals a time-series view, and 'one game' signals a single-app scope. There is no explicit when-to-use, when-not, or named alternative among the wishlist siblings, so the agent must infer routing from the sibling names alone.

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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