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thhart

Log MCP Server

by thhart

read_log_range

Read a specific range of lines from a log file with token-based pagination to manage AI context limits.

Instructions

Reads a specific range of lines from a log file. Uses token-based pagination to respect AI context limits.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
end_lineNoEnding line number (1-based, inclusive). If not specified, reads to end of file or token limit.
filenameYesName of the log file to read
max_tokensNoMaximum tokens to return (default: 4000, max: 100000). Uses ~4 chars per token estimation.
start_lineNoStarting line number (1-based, inclusive)
Behavior4/5

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

No annotations are provided, so the description carries full burden. It discloses token-based pagination, default and max tokens, character-per-token estimation, and behavior when end_line is unspecified. This adds meaningful context beyond basic read functionality.

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?

Two sentences, each adding essential information. The first sentence states the primary purpose, the second explains key behavioral constraint. No wasted words.

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 4 fully documented parameters and no output schema, the description covers the main behavioral aspects. It lacks error handling details or output format, but for a simple read tool with sibling context, it is reasonably complete.

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 parameters are already well-documented. The description adds minor value by contextualizing max_tokens and pagination, but does not significantly enhance understanding of individual parameters beyond schema.

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 clearly states 'Reads a specific range of lines from a log file,' specifying the verb and resource. It differentiates from siblings like head_log or tail_log by focusing on a range, and mentions token-based pagination, which adds context.

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 description implies usage for reading line ranges with pagination but does not explicitly advise when to use this tool versus alternatives like read_log_paginated or head_log. No exclusions or prerequisites are given.

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

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