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Wishlist Ledger

Event or sale impact

get_event_impact
Read-onlyIdempotent

Compare daily wishlist adds, wishlist purchases, units and net revenue during an event (a Steam event id from list_steam_events, or your own start and end dates such as a launch or your own discount) against the days just before it.

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_event_impact"
  }
}

Input Schema

NameRequiredDescriptionDefault
appidYesSteam app id, from list_games
end_dateNoEvent end, if no event_id
event_idNoId from list_steam_events
start_dateNoEvent start, if no event_id
baseline_daysNoDays before the event to compare against

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.6/5.0
Behavior3/5

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

Annotations already declare this a read-only, idempotent, closed-world, non-destructive operation, so the safety profile is covered. The description adds the useful behavioral detail that results are compared against the preceding days, but it says nothing about the shape of the comparison output (deltas, percentages, per-day rows) and there is no output schema to fall back on.

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?

A single front-loaded sentence that leads with the verb and the metrics, then handles the input modes in a parenthetical. It is dense but every clause carries information; the nested parenthetical is the only mild readability cost.

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?

Inputs are well covered and annotations handle the safety profile, so an agent can call it correctly. However, for an analytical comparison tool with no output schema, the description leaves the return structure entirely unspecified, which is the main remaining gap.

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 all five parameters are already documented, including baseline_days' default of 14 and its 3-90 range. The description reinforces the event_id vs start_date/end_date mutually exclusive pattern and the meaning of the baseline window, but adds no syntax or constraint detail beyond the schema.

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 verb (compare) plus the exact metrics (wishlist adds, wishlist purchases, units, net revenue) and the comparison frame (during event vs days just before). An agent can tell this apart from get_wishlist_activity or get_sales, which report activity rather than event-vs-baseline deltas, though no sibling is named explicitly.

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?

Gives clear context for when to reach for it: measuring an event's impact, and it explains the two input routes (a Steam event id from list_steam_events, or your own start/end dates for a launch or self-run discount). It stops short of explicit when-not-to-use guidance or naming which sibling to use for plain trend reporting.

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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