Mne Compute Noise Cov

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

No annotations are provided, so the description must fully carry behavioral disclosure. It clarifies that the baseline is data up to tmax seconds, but it does not disclose whether it stores the result in the session under cov_name, whether it mutates the Epochs object, or what session state is required.

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 two sentences with no filler. The core action and the key tmax/default detail are front-loaded, and the second sentence adds a useful downstream purpose without repetition.

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?

The workflow anchor ('needed before building an inverse operator') and the existence of an output schema cover some context. However, the description still leaves important gaps for an agent invoking it in a pipeline, such as requiring an existing Epochs object and explaining how the covariance is stored for later steps.

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?

Schema description coverage is 0%, so the description must compensate for the missing parameter documentation. It adds meaning for tmax ('data up to tmax seconds, default 0'), but it leaves `name` and `cov_name` semantically undocumented; those are only inferable from their names and defaults.

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 states a clear verb ('Compute') and a specific resource ('a noise covariance matrix from the Epochs baseline'), making the primary action and input type obvious. It does not explicitly differentiate itself from related tools like mne_compute_connectivity, but the output and input are specific enough to avoid major confusion.

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?

The description provides useful pipeline context: the covariance matrix is needed before building an inverse operator for source localization, so an agent knows when to use it. It does not discuss exclusions or alternatives, but for this tool the alternatives are not obvious and the workflow context is clear.

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