Skip to main content
Glama

Mne Average Evoked

mne_average_evoked

Average Epochs into an Evoked response (ERP/ERF) for a specific condition or all conditions, storing the result under a chosen name for further analysis.

Instructions

Average Epochs into an Evoked (ERP/ERF) response. condition = an event_id name to average just that condition (else averages all). Stored under evoked_name.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
conditionNo
epochs_nameNoepochs
evoked_nameNoevoked

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.2/5.0
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 reveals that it averages all conditions by default if no condition is given, and stores under evoked_name. However, it doesn't mention side effects like overwriting existing evoked data or requiring specific prerequisites (e.g., epochs must exist).

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?

The description is short and front-loads the main action. Each sentence earns its place, though the second sentence about parameters could be more detailed without bloating.

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?

Given the output schema exists, return values are covered. However, the tool is part of a complex pipeline with many siblings. The description lacks information about data dependencies (e.g., existence of epochs), which is critical for correct invocation. It is minimally complete but leaves gaps in prerequisites.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, and the description only explains the condition parameter. It does not explain epochs_name and evoked_name beyond their defaults, which is insufficient given the lack of schema descriptions. The description adds some value for condition but fails to compensate for the other two parameters.

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?

The description states a clear verb ('Average') and resources ('Epochs into an Evoked'), distinguishing it from siblings like mne_make_epochs. It lacks explicit differentiation from other averaging or plotting tools, but the action is specific.

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?

It explains the optional condition parameter but doesn't say when to use this vs alternatives like mne_plot_evoked or mne_make_epochs. The context is implied by the MNE workflow, but no explicit exclusions or alternatives are mentioned.

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