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

Annotations already cover the safety profile (readOnlyHint, idempotentHint, destructiveHint=false), so the bar is lower, and the description adds meaningful behavioral context: the free tier returns counts, ranges and redacted samples, while PRO unlocks vendor names, model names and exact prices. This tells the agent upfront that a free-tier call may not return the identifiers it needs, which is genuinely actionable. It stops short of covering lookup-failure behavior or response shape details.

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?

Two sentences, front-loaded with the substantive content list and followed by the access-tier caveat. It is efficient, though the parenthetical price and URL read as promotional padding rather than tool guidance.

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 no output schema, the description carries the return-value burden and does so by enumerating returned fields and the tier-based redaction. Combined with the annotations covering safety and idempotency, an agent has enough to invoke it correctly; only error/not-found behavior is unaddressed.

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 100%, so both parameters (model_name with examples, _atom_api_key with its tier purpose) are already documented. The description's tier explanation for the key restates what the schema says, adding no syntax or format detail beyond it. Baseline 3 is appropriate.

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 specific resource ('One model in depth') and enumerates exactly what is returned: specs (creator, origin, tier, license, context window, output limit, training cutoff, modalities), index memberships, and per-vendor pricing. This level of content specification makes it distinguishable from a bare lookup tool even without naming siblings explicitly.

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?

The description implies the usage context (look up a single known model for detailed specs and pricing) and explains the free vs PRO access condition, but never states when to prefer this over siblings such as get_model_intelligence, search_models, or compare_prices. Usage is inferable rather than instructed.

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