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erdos2n

Meticulous Espresso MCP Server

by erdos2n

get_settings

Read the espresso machine's current settings, including auto-preheat, sounds, and timezone; optionally filter to a specific setting key.

Instructions

Read the current machine settings (auto-preheat, auto-start shot, purge after shot, sounds, timezone, heating timeout, etc.). Optionally filter to a specific setting key.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
setting_nameNoOptional: specific setting key to retrieve (e.g. 'auto_preheat', 'enable_sounds')
Behavior3/5

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

No annotations are provided, so the description carries the burden. It states 'Read' which implies a non-destructive operation, but it doesn't disclose what happens for invalid setting keys, whether it returns all settings if no filter is given, or any other behavioral details beyond the basic read/filter behavior.

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 a single, front-loaded sentence that efficiently states the tool's purpose and the optional filter. No wasted words; every element contributes directly to understanding.

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 simple, optional-parameter read tool with no output schema and no annotations, the description is quite complete: it states the resource, the action, and the one capability (filtering). It doesn't specify the return format, but that's not critical for such a straightforward 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?

The schema already covers 100% of the parameter (setting_name) with a description and examples. The tool description adds some broad example categories (auto-preheat, sounds, timezone) but doesn't substantially go beyond what the schema already provides. Baseline for high schema coverage is 3.

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 the tool's purpose: 'Read the current machine settings' with a specific verb and resource. It lists concrete setting categories (auto-preheat, enable_sounds, etc.) and distinguishes from siblings like update_setting by framing it as a read operation.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides clear context for when to use this tool (when you need to read current machine settings) and mentions optional filtering. Though it doesn't explicitly name alternative tools or exclusions, the 'Read' verb implies this is for viewing, not modifying, settings.

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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