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Mne Apply Ica

mne_apply_ica

Remove ICA artifact components from neurophysiology data by passing component indices or using the ICA object's current exclude list.

Instructions

Remove ICA components from an instrument in place. exclude = comma-separated component indices to drop (e.g. '0,3'); if omitted, uses the ICA object's current exclude list.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
excludeNo
ica_nameNoica
inst_nameNoraw

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3/5.0
Behavior3/5

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

With no annotations, the description discloses one important behavioral trait: the operation mutates the instrument 'in place'. It also explains the exclude default. However, it omits other behavioral context such as failure conditions, object requirements, or whether the original data is recoverable.

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 tightly written with no filler: the purpose verb is front-loaded, and the exclude note earns its place. It is appropriately concise for what it covers.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no annotations and a nontrivial MNE operation, the description is incomplete: it doesn't state that ICA must be fitted first, that ica_name/inst_name refer to session objects, or what happens when the objects are incompatible. The output schema existing does not make up for missing prerequisites and side-effect context.

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%, so the description must explain the parameters. It does explain 'exclude' well (format and fallback), but says nothing about ica_name or inst_name, leaving two of three parameters to be inferred from their defaults and names.

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 specific operation ('Remove ICA components from an instrument in place') with a clear resource and mutation sense. It is distinguishable from siblings like mne_fit_ica and mne_plot_ica_components, though it does not explicitly name any sibling or mention that it applies an already-fitted ICA.

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 guidance on when to use this tool versus alternatives, and no prerequisites are stated (e.g., that a fitted ICA object must already exist). The only usage-like detail is the exclude fallback, which is parameter behavior rather than tool-selection guidance.

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