get_signal_quality

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

With no annotations, the description carries the transparency burden. It does disclose that this is a snippet-scoped read operation capped at 10 s and enumerates the signal-quality metrics, so an agent can predict the core behavior. However, it does not cover session prerequisites, error behavior, or return structure, which are relevant for a raw-data analysis tool.

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 succinct, front-loaded sentence contains all the high-level information with no filler or redundancy.

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 tool with no annotations and no output schema, the description provides only the output categories and a duration cap; it is missing the meaning of t0, how session_id relates to an open session, and what response shape to expect. This is enough for a rough guess but not a fully informed call.

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 0%, so the description must compensate. 'max 10 s' clarifies the intended value of duration_s, but t0 is not explained and session_id is only recoverable from its name; no relationship between t0 and the snippet is given.

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 names specific outputs (noise level, SNR, dead/noisy channels) and the data source (a broadband snippet), which differentiates it from spike-sorting and decoding siblings. The operative verb is only implied by 'get', so it is clear but not maximally explicit.

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?

It implies the appropriate use case—checking quality on a snippet when noise/dead channels need assessment—and the 'max 10 s' bound sets a duration constraint. It does not state when to prefer another tool or mention exclusions, leaving alternatives to inference.

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