scival_topic_metrics

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states nothing about side effects, output format, data freshness, authentication, or any operational details. The description is essentially a label, offering zero behavioral transparency.

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?

While the description is extremely short, this is under-specification rather than deliberate conciseness. It provides no structural benefit or front-loaded information. Every sentence (there is only one) is vague and doesn't earn its place.

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 three parameters (one required), no output schema, and no annotations, the description is completely inadequate. It fails to explain the tool's purpose, parameters, or expected behavior, leaving an agent with no actionable information.

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%, meaning none of the three parameters (topic_id, year_from, year_to) are described in the schema. The description does not compensate by explaining any of them. An agent cannot infer what these parameters mean or how they should be formatted.

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 resource ('SciVal topic') and implies an operation ('metrics'), but it's a noun phrase with no explicit verb. It doesn't distinguish itself from sibling tools like scival_author_metrics or scival_institution_metrics beyond the resource name, and it doesn't specify what metrics are returned or how they are computed.

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 guidance on when to use this tool versus alternatives. No mention of use cases, prerequisites, or exclusions. An agent has no way to decide between this and other SciVal metric tools.

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