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Analyze live combat state and lane differentials

lol_analytics_live_combat
Read-onlyIdempotent

Extracts real-time combat status, lane gold/level comparisons, match clock, and team score differentials from the live game engine to assess map state during active League matches.

Instructions

Extracts real-time combat status, lane gold/level comparisons, match clock, and team score differentials from the in-match Live Game Engine on port 2999. Use this tool during active live games to assess map state, score leads, or lane advantages. For raw live game data or item builds, use lol_game_all or lol_game_player instead. For post-game analysis, use lol_analytics_match_detail. Behavior: Safe and read-only; connects directly to local game client without external network calls. Returns inGame: false if no match is currently running.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

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 readOnly, idempotent, and non-destructive, but the description adds real behavioral context beyond them: the data source (local Live Game Engine on port 2999), the absence of external network calls, and the edge-case return of inGame: false when no match is running. It stops short of rate limits or failure modes, but the added source and no-match semantics are genuinely useful.

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 tight sentences, front-loaded with what is extracted, then usage, then alternatives, then behavior. Every sentence carries distinct information with no filler, though the routing and behavior clauses could be trimmed slightly.

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?

For a zero-parameter, read-only tool with no output schema, the description covers source, usage, alternatives, safety, and the no-match edge case. It could go further in sketching the returned shape, but it is complete enough to call correctly and interpret the inGame: false case.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool takes zero parameters, so there is no parameter semantics to document and the baseline is 4. The description correctly avoids inventing parameters and instead describes the data categories the call returns.

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 opens with a specific verb ('Extracts') and enumerates the exact resource: real-time combat status, lane gold/level comparisons, match clock, and team score differentials. It names the source ('Live Game Engine on port 2999') and distinguishes itself from siblings lol_game_all, lol_game_player, and lol_analytics_match_detail, so an agent can select it without opening another schema.

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?

It states the usage context explicitly ('during active live games to assess map state, score leads, or lane advantages') and routes to named alternatives with the conditions that select them: raw data/item builds go to lol_game_all or lol_game_player, post-game analysis goes to lol_analytics_match_detail. Both when-to-use and when-not-to-use are covered.

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