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Read recent log lines from disk

lol_logs_tail
Read-onlyIdempotent

Read recent disk log lines from League Client, CEF UX, or Game engine to inspect historical or startup errors. Automatically redacts sensitive data.

Instructions

Read the most recent log lines from the active or selected League Client, CEF UX, or Game engine disk log file. Use this tool to inspect historical or startup errors recorded on disk. For live streaming log monitoring, use lol_logs_watch_start and lol_logs_watch_poll instead. For in-memory renderer console messages, use lol_cdp_console_tail. Behavior: Safe and read-only. Automatically redacts passwords, auth tokens, and sensitive keys from log output.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
levelNoFilter lines by log level or ALL (default: ALL)ALL
linesNoNumber of lines to read backward from EOF (1-2000, default: 100)
searchNoCase-insensitive substring filter applied to raw log lines
targetNoLog target: "client" (LCU core), "ux" (CEF UI frontend), or "game" (r3dlog engine)client
sessionNoSession ID or log filename from lol_logs_sessions; omit for active session

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=true, idempotentHint=true, destructiveHint=false, so safety is covered structurally; the description reinforces this and adds a genuinely new trait: automatic redaction of passwords, tokens, and sensitive keys. It does not mention pagination or error behavior, but redaction disclosure is real added value.

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?

Three tight sentences: purpose, usage routing, and behavior. The primary purpose is front-loaded and alternatives follow, with zero filler.

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 no output schema and a fully documented 5-param schema, the description covers what an agent needs: purpose, routing, and the redaction guarantee. It stops short of describing return shape or how line counts map to output, but that gap is minor for a read-only tail tool.

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 every parameter (level, lines, search, target, session) is already documented in the schema. The description adds only the notion of an 'active or selected' log file, which the schema's session description already implies, so baseline 3 is 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?

Starts with a specific verb+resource (read recent log lines) and scopes it to three concrete sources (League Client, CEF UX, Game engine disk log file). It clearly separates itself from siblings like lol_logs_watch_start/poll and lol_cdp_console_tail by naming them as different modes.

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 states when to use it ('inspect historical or startup errors recorded on disk') and names two alternative tools with their distinguishing conditions (live streaming vs in-memory renderer console). An agent can route correctly without opening any schema.

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