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

With no annotations, the description must carry the behavioral load. 'Live view' usefully implies a read-only, observation-style call and the text spells out what content comes back, but it says nothing about side effects, freshness/caching, or image payload size, which matters for a picture-heavy view.

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 front-loaded sentence that leads with the core concept and then lists the contents. It is dense with colon-separated clauses but every element earns its place; no filler or repetition.

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?

There are no annotations and no output schema, so the description has to stand in for the return shape – and it does, listing the four things an agent will see. Missing only operational details such as whether the images are large or how current the 'live' data is.

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?

The tool takes zero parameters, so there is nothing the schema needs to explain; baseline is 4. The description wastes no effort inventing 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 names a concrete artifact – a live view of the camera's face-learning of individual trout via spot patterns – and enumerates its sections (match attempts, learned faces, near-named fish, how matching works). That is well beyond a restatement of the title, though it never distinguishes itself from ambiguous neighbors like whos_that_trout or trout_highlights.

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 explicit when-to-use statement, no exclusions, and no named alternative among the large sibling set. An agent must infer that this is a read-only status dashboard rather than the interactive identification tool (whos_that_trout) or the roster (pool_roster).

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