log_event

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

With no annotations provided, the description carries the full burden. It discloses key behavioral traits: events are recorded against the stream clock, the value is also written to a marker channel when mark_in_stream is set, and BrainFlow reserves 0 so a nonzero value is required. This is meaningful context beyond the schema. Minor gap: it doesn't describe the return/acknowledgement of successful logging.

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?

Extremely concise. The purpose is front-loaded in the first sentence, followed by two short sentences that clarify scope (what counts as a manual event) and the exclusion note about send_stim_event. Every sentence earns its place with zero 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?

The tool has 6 parameters, an output schema, and 100% schema coverage. The description adds the crucial manual-vs-automatic event distinction and the marker channel caveat. For a logging tool this is largely sufficient. Slight gap: it doesn't mention whether events can be queried later via get_events, though the output schema presumably covers return structure.

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 coverage is 100% and all 6 parameters are individually described in the schema. The description adds contextual nuance to 'value' (marker channel writing, BrainFlow reserve) and to 'label' via practical examples. The novel addition is the mark_in_stream behavior interplay with the value field, which goes beyond schema text.

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 specific verb+resource ('Record an event against the stream's clock') and lists concrete example use cases (task onset, subject report, experimenter note). It distinguishes itself from the sibling send_stim_event by explicitly noting stimulation commands are logged automatically by that tool and should not be logged by hand here.

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?

Explicitly says when to use: for anything the server did not generate itself. Explicitly says when NOT to use: stimulation commands, which are logged automatically by send_stim_event. This names the specific alternative tool and states the exclusion clearly.

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