VGC Teambuilder

Get a Pokémon's usage over time

get_usage_trend

Read-onlyIdempotent

Show one Pokémon's monthly usage and rank in a regulation across a range of months, with its net change and peak. History exists only for months the regulation's ladder was active.

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": {
      "pokemon": "<pokemon>"
    },
    "name": "get_usage_trend"
  }
}

Input Schema

Name	Required	Description
`to`	No	Last month, YYYY-MM. Defaults to the most recent month
`from`	No	First month, YYYY-MM. The nearest month with data is used if it has none
`format`	No	Regulation id from list_formats. Defaults to "champions-regmc" (Pokémon Champions — Regulation M-C).
`months`	No	Months to look back from `to` when `from` is omitted. Defaults to 12
`pokemon`	Yes	Pokémon name in English. Mega Evolutions are tracked separately, e.g. "Charizard-Mega-Y"

Output Schema

Name	Required	Description
`to`	Yes	Last month compared, YYYY-MM
`from`	Yes	First month compared, YYYY-MM
`peak`	Yes
`format`	Yes	Regulation id the result applies to
`points`	Yes
`pokemon`	Yes
`formatName`	Yes	Display name of the regulation
`netChangePoints`	Yes	Last month's usage minus the first's, in percentage points

Schema Changelog

Changes observed during successful MCP inspections.

First observedNov 13, 2026

TDQS

A3.8/5.0

Behavior4/5

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

Annotations already cover safety (readOnly, idempotent, non-destructive, closed-world), so the description's job is to add operational context — and it does, by disclosing that history is bounded by ladder activity and that the tool returns computed deltas and a peak. It omits anything about caching or response shape, though an output schema exists so that is acceptable.

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?

A single front-loaded sentence states the resource, the range semantics, the returned aggregates, and the data-availability constraint with no filler. Nothing could be removed without losing information.

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 a full output schema, complete parameter documentation, and annotations covering safety, the description only needs scope and data-availability context, both of which are present. The remaining gap is routing guidance among the many usage-related siblings.

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%, with per-parameter descriptions for from/to/months/format/pokemon including formats, defaults, and fallback behavior, so the schema carries the parameter burden. The description adds only the aggregate notion of 'a range of months' and no extra syntax or edge-case meaning 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?

The description names a specific verb and resource ('Show one Pokémon's monthly usage and rank in a regulation across a range of months') plus the derived values returned (net change, peak), which is far more precise than the title alone. It does not explicitly distinguish itself from close siblings such as get_pokemon_usage or get_usage_momentum, 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 Guidelines3/5

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

Usage is implied by the time-series phrasing and the caveat that history only exists for months when the regulation's ladder was active, which tells the agent when results may be sparse. There is no explicit when-to-use or when-to-prefer-another-tool guidance against the many sibling tools.

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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