mne_events_from_annotations

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

No annotations are provided, so the description carries the full burden. It only states the conversion function, omitting side effects, safety, prerequisites (e.g., raw must have annotations), or whether the input is mutated. This is a significant gap for a tool with zero annotation coverage.

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 a single, well-structured sentence with a clear subject-action-object pattern. It conveys the core purpose without any wasted words, achieving high conciseness.

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?

While the tool is simple and an output schema exists, the description leaves out essential context such as parameter meanings, prerequisites (annotations must be present), and differentiation from mne_find_events. This makes it incomplete for an agent to use correctly without additional inference.

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%, and the description does not mention raw_name or events_name at all. The description completely fails to compensate for the lack of parameter documentation, leaving the agent guessing about the purpose and usage of these optional parameters.

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 specific verb 'Convert' with the resource 'Raw object's annotations' and the outputs 'events array + event_id map'. It also mentions the intended data formats (EDF/BrainVision/EEGLAB), which distinguishes it from sibling tool mne_find_events that likely extracts events from triggers.

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 clear context by specifying applicable data types (EDF/BrainVision/EEGLAB), implying when to use it. However, it does not explicitly compare with mne_find_events or state when not to use it, so it stops short of a full guideline with exclusions.

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