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Analyze summoner ranked and match history performance

lol_analytics_player
Read-onlyIdempotent

Assess a League of Legends player's ranked tier, LP, win rate, average KDA, CS per minute, and champion pool to gauge skill and progression before or after matches.

Instructions

Evaluates comprehensive summoner profile analytics including ranked tiers, LP, winrate %, average KDA, CS per minute, and primary champion pool. Use this tool when assessing a player's skill level, ranked progression, or preferred champions before or after matches. For viewing individual recent matches in a compact list, use lol_analytics_match_history instead. For in-depth post-match breakdown, use lol_analytics_match_detail. Behavior: Safe and read-only; queries local client cache and REST endpoints without modifying game state. Returns structured performance metrics.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
puuidNoTarget player PUUID. When omitted, evaluates currently logged-in summoner.
matchCountNoNumber of recent matches to evaluate (1 to 20, default 10).

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.6.0

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false, and idempotentHint=true, so the safety profile is covered. The description adds useful context by stating that it queries local client cache and REST endpoints and returns structured performance metrics, though it does not detail pagination or response shape.

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?

The description is front-loaded with the tool's purpose, followed immediately by usage guidance and alternative routing. Every sentence contributes either purpose, routing, or behavioral context, with no wasted prose.

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

Completeness5/5

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

Although no output schema exists, the description lists the concrete metrics returned and gives sufficient usage and behavioral context. With annotations covering safety and schema covering parameters, an agent has everything needed to select and invoke it 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%, so both parameters (puuid and matchCount) are fully documented in the input schema. The description adds no parameter-specific syntax, defaults, or constraints beyond what the schema already provides, making baseline 3 appropriate.

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?

State a specific verb (Evaluates) and resource (summoner profile analytics) and names the exact metrics returned: ranked tiers, LP, winrate, average KDA, CS per minute, and primary champion pool. It distinguishes itself from lol_analytics_match_history and lol_analytics_match_detail explicitly.

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

Usage Guidelines5/5

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

Provides explicit use cases (assessing skill level, ranked progression, preferred champions before or after matches) and names two alternatives with the conditions that select them. An agent can route correctly without opening sibling schemas.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.