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

Annotations already declare readOnly/idempotent/openWorld safety, and the description adds genuine behavioral context beyond them: an automatic Groq-hosted LLM fallback when Jev is slow or unavailable and a <4.5s latency guarantee. It does not disclose auth, rate limits, or error semantics, so not a 5.

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?

Roughly three sentences, front-loaded with the core purpose, followed by operational context and a sample endpoint hint. Efficient overall, though the sample-endpoint sentence is marginal value for an agent already holding the schema.

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?

An output schema exists and annotations cover the safety profile, so the description need not explain return values. It supplies provider/fallback and latency context, but lacks any guidance on alternatives among the many classification-adjacent siblings.

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?

Only one parameter and schema description coverage is 100% (text up to 4000 characters), so the schema already documents everything. The description adds no parameter-level meaning beyond that, matching the baseline 3 for high-coverage schemas.

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?

States a specific verb (classify) and resource (text as spam/not spam) plus the output shape (confidence score). It is clear, but it does not explicitly differentiate from generic siblings like classify, guard, or toxicity, so it falls short of a 5.

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?

No indication of when to prefer this over classify, guard, or toxicity, nor any exclusions. The only routing-adjacent content is internal (LLM fallback, sample endpoint), not guidance for an agent choosing between tools.

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