mne_apply_inverse

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

With no annotations, the description carries the burden of behavioral disclosure. It mentions 'Stores the source estimate (stc)' and 'reports the peak activation time,' which are useful, but it does not disclose side effects like overwriting existing variables, required session state, or failure conditions.

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 three concise sentences with no filler. It front-loads the purpose, then method options and side effects, making it easy to scan.

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 tool is complex, and the output schema exists but the description lacks full context. It does not explain parameter semantics, preconditions (e.g., that fwd and noise_cov must exist), or state changes beyond storing stc. The pipeline hint helps but is insufficient for a tool with no annotations and 0% schema coverage.

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. It explains the 'method' parameter with options, but leaves snr, cov_name, fwd_name, stc_name, and evoked_name undefined. These names are partially self-explanatory, but the description does not confirm their roles.

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 clearly states the tool's function: 'Estimate cortical sources from an Evoked using a forward model and noise covariance.' It specifies the resource (cortical sources from an Evoked) and the method options, distinguishing it from sibling tools like mne_make_forward and mne_compute_noise_cov.

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 gives explicit pipeline guidance with 'Pair with mne_make_forward + mne_compute_noise_cov.' This indicates prerequisites and intended usage context, though it does not explicitly name alternatives or exclusion scenarios.

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