np_query_spike_events

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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false, and openWorldHint=false, fully covering the safety profile. The description adds only one behavioral hint beyond that — that results are per-spike (individual timings), implying potentially large result sets — but says nothing about pagination, the limit cap of 2000, or result shape. Adequate but thin given the annotations carry the safety burden.

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?

A single short line with no filler and the resource named up front, so it is not padded. But its brevity reflects under-specification rather than disciplined conciseness — there is almost no content to front-load.

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 3-parameter query tool with no output schema and only 33% schema coverage, the description leaves major gaps: it never explains what fsname refers to, the meaning of the window unit, or what a caller should expect back. An agent could invoke it but not with confidence about the identifier or result scope.

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 only 33% (only window_sec, 'Look back this many seconds', is documented), and the description supplies no parameter meaning at all. The cryptic fsname (default 'fs264') and limit are undocumented in both description and schema, so the description fails to compensate for the coverage gap.

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 resource (spike events) and clarifies the return granularity ('individual spike timings over a window'), which implicitly distinguishes it from the count-oriented siblings np_count_spikes and np_query_spike_count. However, it is framed as a database tagline ('SpikeEventQuery') and never names an alternative or explicitly contrasts with the count tools, leaving differentiation to inference.

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?

There is no statement of when to use this tool versus alternatives such as np_query_spike_count or np_query_triggers, nor any prerequisite or exclusion. The agent must infer usage from the name alone.

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