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erdos2n

Meticulous Espresso MCP Server

by erdos2n

set_grinder_context

Saves the grinder model and setting for an espresso profile, preserving dial-in adjustments so Claude recalls them in future sessions.

Instructions

Save the grinder model and setting for a profile. Call this whenever you change your grind size so Claude remembers it next session.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
notesNoOptional notes (e.g. 'too coarse, dropping to 10.5 next')
grinderYesGrinder model (e.g. 'DF83 V3')
settingYesGrinder setting / number
profile_nameYesThe profile name to associate this grinder setting with
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It indicates a save (write) operation and persistence ('so Claude remembers it next session'), but it does not disclose potential side effects such as overwriting existing context, behavior if the profile doesn't exist, or any preconditions. This lack of transparency is a significant gap for a mutation tool.

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 only two sentences, both of which earn their place: the first states the core action and the second provides the key usage trigger. It is front-loaded and free of filler or redundancy.

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 tool with a fully described schema, the description covers the essential purpose and usage context. The lack of output schema means no return documentation is needed. However, the description is somewhat thin on edge cases (e.g., overwrite semantics), which keeps it from a perfect score despite the low complexity.

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 each parameter is already documented. The description adds negligible meaning beyond the schema; it mentions 'grinder model and setting' which simply mirrors the parameter names and schema descriptions. The baseline of 3 is appropriate since the schema does the heavy lifting.

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 function: 'Save the grinder model and setting for a profile' with a specific verb (save) and resource (grinder model/setting for profile). It also distinguishes itself from siblings like get_grinder_context by emphasizing the save action, and from other save/update tools by focusing on grinder context specifically.

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 an explicit when-to-use instruction: 'Call this whenever you change your grind size so Claude remembers it next session.' This gives clear context for the tool's intended usage, but it does not mention when not to use this tool or compare it to alternatives such as save_profile or update_setting.

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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