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LemonMCP

LemonMCP

Official
by lemonXGroup
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TypeScript
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fetch_system_logs

Safely reads the tail of the Lemon core engine log to analyze system or runtime network errors, ideal for large log files.

Instructions

Safely reads the tail (end) of the Lemon core engine (lemoncore.log) to analyze system or runtime network errors. Suitable for large log files.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "fetch_system_logs"
  }
}

Input Schema

NameRequiredDescriptionDefault
bytesNoNumber of bytes to read from the end. Default is 102400 (100KB, ~1500 lines). Increase only if deeply debugging.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

B3.4/5.0
Behavior3/5

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

With no annotations present, the description carries the full burden. 'Safely reads' correctly signals a non-destructive read and naming the exact log file adds real context, but it omits permission requirements, whether reads rotate/truncate logs, and any rate or size limits beyond the schema's bytes parameter.

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?

Two tight sentences, front-loaded with the action and resource, then the use case. 'Safely' and 'Suitable for large log files' are the only vaguely filler-ish bits, but every sentence contributes.

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 one-parameter read tool with no annotations and no output schema, the description covers purpose and file target but says nothing about the return shape (raw log text? truncated?) or failure behavior when the log is absent. Adequate but with a visible gap.

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%, and the single 'bytes' parameter is already fully documented in the schema (default 102400, ~1500 lines, when to increase). The description adds nothing about parameters, so the baseline 3 applies.

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?

States a concrete verb (reads the tail) and a precise resource (lemoncore.log, the Lemon core engine log), plus the intent (analyzing system/runtime network errors). It is clear on its own, though it never names a sibling such as clear_system_logs to disambiguate log-related operations.

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 phrase 'to analyze system or runtime network errors' and 'Suitable for large log files' imply when this tool is appropriate, but there is no explicit when-not guidance or comparison against alternatives like fetch_device_file or clear_system_logs. Usage is only inferred, not stated.

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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