Mne Compute Tfr

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

The description adds useful behavioral context beyond annotations: input epochs are unchanged, averaged power is total rather than induced, and the tool returns output names, shape, optional figure paths, and reproducible code. However, annotations flag destructiveHint=true and the description does not explain what may be overwritten or created in the session, leaving that destructive side effect undisclosed.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is compact and front-loaded, with the core operation stated first and every sentence carrying substantive information. It is slightly dense due to many semicolon-separated clauses, but it contains no filler.

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

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

For a complex nested-params tool, the description covers purpose, key parameter groups, a functional caveat, an ITC precondition, return values, and input safety, while the rich input/output schemas fill in remaining details. It omits guidance on destructive session side effects and sibling tool choice, which keeps it just below excellent.

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

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

With schema description coverage at 0%, the description compensates by naming important parameter groups: explicit freqs, scalar/per-frequency n_cycles, picks, decimation, trial retention (average), ITC, and baseline normalization. It does not cover all nested parameters such as method, baseline_mode, or time_bandwidth, so the compensation is partial.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description names a specific operation ('Compute Morlet or multitaper Epochs power') and enumerates key capabilities such as explicit frequencies, n_cycles, picks, decimation, ITC, and baseline normalization. It does not explicitly distinguish itself from the closely related sibling mne_tfr_morlet, so it stops short of full sibling differentiation.

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

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

It provides some practical guidance: 'Pass a params JSON object', 'ITC requires average=true', and the caveat that averaged power is total power, not strictly induced power. However, it never states when to choose this tool over mne_tfr_morlet or another alternative, so when-not/alternatives guidance is missing.

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