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vlr_team_maps

Retrieve a Valorant team's per-map win rates, round-side stats, and first-round counts from VLR.gg to compare map strengths and identify performance gaps.

Instructions

VLR.gg Valorant team map win rates. Returns a team's per-map record from VLR.gg: maps played, win percent, wins and losses, plus attack-side and defense-side round win percent, rounds won and lost and first-round counts. Use it to compare map strengths; vlr-team-matches lists the underlying matches.

Input Schema

NameRequiredDescriptionDefault
idYesNumeric VLR team id from vlr-rankings, vlr-event or vlr-match

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.17.18

TDQS

A3.9/5.0
Behavior3/5

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

No annotations are supplied, so the description carries the full behavioral burden; it does disclose the shape of the return (per-map records with several stat families), which is the most useful thing it could say. However, it says nothing about the scope of the aggregate — whether the record covers all time, a season, or a specific event — which materially affects interpretation of the win rates. It is a read-only stats fetch, so the safety profile is not a concern, but the data-window ambiguity is a real gap.

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?

Three sentences, front-loaded with what the tool returns, then the field inventory, then the routing hint. Every sentence earns its place — the field enumeration is justified because there is no output schema — though the middle sentence is a long run-on list that could be tightened.

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 one required parameter, no annotations, and no output schema, the description does the heavy lifting on return values and sibling routing well. The remaining gap is the time/scope qualifier for the aggregated stats, which an agent would need in order to interpret 'win percent' correctly.

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%: the single `id` parameter is documented as a numeric VLR team id sourced from vlr-rankings, vlr-event or vlr-match. The description adds nothing about the parameter beyond what the schema already says, so the baseline 3 applies.

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 states a specific verb and resource — 'team map win rates' from VLR.gg — and immediately enumerates the per-map record returned (maps played, win percent, wins/losses, attack/defense round win percent). It also distinguishes itself from the nearby sibling vlr_team_matches, so an agent can tell the two apart without opening a schema.

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?

It gives an explicit use case ('compare map strengths') and names the alternative (vlr-team-matches) that holds the underlying match list, which is the main routing decision an agent faces here. There is no explicit 'do not use this when…' clause, so it stops short of full when/when-not guidance.

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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