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

Goes meaningfully beyond annotations by disclosing that the server supplies its own API keys, that calls are rate-limited, that only whitelisted model IDs are accepted, and which providers back which models. Annotations cover the safety profile and an output schema exists, so remaining gaps are minor.

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?

Front-loaded with purpose and provider, then key operational facts. The model catalog enumeration is somewhat redundant with the schema and list_llm_models, but each sentence still carries usable information.

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?

With a full schema, an output schema, and annotations already present, the description supplies the missing operational context: auth model, rate limits, provider routing, and where to find the model catalog. Nothing needed to call it correctly is absent.

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 100%, so the baseline is 3. The description's model list adds little beyond the schema's own detailed model/whitelist note and is actually less precise — it names Gemma 4 27B, Llama 4 Scout and Mistral Small 24B without noting they may be BYOK-only per the schema, which could mislead model selection.

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 (generate text) and resource (LLM models), and names both providers it can route to. It is clearly distinguishable from siblings like list_llm_models (catalog browsing) and compare_models (multi-model comparison).

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?

Gives a concrete routing cue: use list_llm_models to see the full catalog before choosing a model, and signals the no-key/rate-limited context. It does not say when to prefer this over compare_responses or build_rag_prompt, so no explicit exclusions are provided.

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