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Glama

lcu

Call the League of Legends Client API with authentication handled automatically. Dangerous writes like purchases, crafting, reports, invites, chat, real queues, logout, and client quit are refused.

Instructions

Calls the LCU API from inside the client (auth handled). Dangerous writes (purchases, loot crafting, reports, invites, chat messages, real queue, logout, client quit) are refused.

Input Schema

NameRequiredDescriptionDefault
bodyNo
pathYese.g. /lol-gameflow/v1/session
methodYes
maxCharsNoTruncate the response (default 20000).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.5/5.0
Behavior4/5

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

The annotations only declare readOnlyHint=false, so the description adds substantial value by stating that auth is handled and that specific dangerous writes are refused. It still does not describe behavior for allowed writes, error responses, or side effects, but the safety disclosure is strong.

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 two tight sentences with no wasted language. The core purpose and auth handling are front-loaded, followed by the important refusal constraint.

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

Completeness3/5

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

For a generic mutating API caller with no output schema and incomplete parameter documentation, the description covers purpose, auth, and write refusals but omits return behavior, allowed-write side effects, and error semantics. It is adequate for selection but incomplete for confident invocation.

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

Parameters2/5

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

Schema coverage is only 50%, and the body parameter has no type or description in the schema. The description does not explain body semantics, method usage, path expectations, or maxChars behavior, so it does not compensate for the missing schema documentation.

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 clearly states the specific action and resource: it calls the LCU API from inside the client. It also adds a meaningful safety boundary by listing dangerous writes that are refused. It does not explicitly distinguish itself from sibling tools such as lcu_endpoints or query, 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?

The refusal list implies some when-not-to-use conditions for dangerous writes, but the description gives no explicit guidance on when to choose this tool over lcu_endpoints, query, or network. Usage is implied by the LCU API framing rather than stated as routing guidance.

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