Skip to main content
Glama

Mne Mark Bad Channels

mne_mark_bad_channels

Mark EEG/MEG channels as bad by name, e.g. 'Fp1,T7', to exclude them from analysis. Append to existing bads or replace the entire list as needed.

Instructions

Mark channels as bad (comma-separated names, e.g. 'Fp1,T7'). By default appends to existing bads; set replace=true to overwrite.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
badsNo
nameNoraw
replaceNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.3/5.0
Behavior3/5

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

Since no annotations exist, the description carries the behavioral transparency burden. It does disclose a meaningful behavioral trait: bads are appended by default and overwritten only when replace=true. However, it does not mention side effects on downstream processing, whether the change is session-local, or whether the operation mutates the named object.

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 two concise, front-loaded sentences with no filler. The action, example, default behavior, and override option are all communicated efficiently.

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 simple three-parameter tool, the description covers most usage needs, and the presence of an output schema makes omitting return-value details acceptable. However, the unexplained 'name' parameter and the lack of any annotation-backed context leave a meaningful gap for fully autonomous invocation.

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 0%, so the description must explain parameter meaning. It usefully describes 'bads' as comma-separated channel names and 'replace' as the overwrite switch, but it never explains the 'name' parameter, leaving which object is modified unclear.

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 opens with a specific action and resource: 'Mark channels as bad', and clarifies the expected input format with a concrete example ('Fp1,T7'). It does not explicitly differentiate from sibling tools like mne_interpolate_bads, but the operation and resource are otherwise unambiguous.

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

Usage Guidelines2/5

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

No when-to-use guidance or comparison to alternatives is provided. The description only explains the append-versus-replace behavior, leaving an agent to infer when marking channels as bad is appropriate or how it relates to sibling tools such as interpolation.

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