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Fetch compact recent match history list

lol_analytics_match_history
Read-onlyIdempotent

Fetch a compact list of recent League of Legends matches for a summoner, including champion names, KDA, win/loss, duration, and queue IDs, to review game history without loading raw JSON.

Instructions

Retrieves a token-efficient, compact list of recent match history games for a summoner with resolved champion names, KDA, win/loss, duration, and queue IDs. Use this tool when you need an overview of recent games without filling the context window with raw JSON data. For high-level ranked stats and winrates, use lol_analytics_player instead. For a deep analytical dive into a single game's damage and objectives, use lol_analytics_match_detail. Behavior: Safe and read-only; queries local client match history and static champion data. Returns an array of concise match objects.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum number of matches to retrieve (1 to 20, default 10).
puuidNoTarget player PUUID. When omitted, fetches current summoner history.
queueIdNoOptional queue filter ID (e.g. 420 for Ranked Solo, 450 for ARAM).

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.6.0

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false, so safety is covered. The description still adds value by disclosing the data sources ('local client match history and static champion data') and the return shape ('array of concise match objects'), though it omits pagination or freshness details.

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?

Four sentences, all front-loaded with the core purpose first, then alternatives, then behavior. Slightly longer than strictly necessary but every sentence carries routing or behavioral information.

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?

With no output schema, the description compensates by naming the returned fields (champion names, KDA, win/loss, duration, queue IDs) and the container type, and it covers sourcing and read-only behavior — enough for an agent to call 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 limit, puuid, and queueId are already fully documented with defaults and examples. The description adds no parameter-level detail beyond what the schema provides, 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?

States a specific verb and resource ('Retrieves a token-efficient, compact list of recent match history games for a summoner') and enumerates the returned fields, letting an agent distinguish it from siblings without opening schemas.

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?

Explicitly names the when ('need an overview of recent games without filling the context window') and routes to alternatives by condition: lol_analytics_player for ranked stats/winrates, lol_analytics_match_detail for single-game deep dives.

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