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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive, closed-world), so the lower bar applies. The description adds genuine behavioral content by disclosing what the estimate computes and what it reports back (GPU count, cost per 1M tokens), which compensates somewhat for the absent output schema.

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 output (monthly AI cost) and then enumerates the comparison axes. Dense but every clause maps to a real dimension of the estimate; no filler.

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 5-parameter tool with no required params and no output schema, the description covers scope and most metrics but does not explain the two bare boolean flags or the return shape. It is minimally adequate but leaves gaps an agent would have to probe by invocation.

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 60%, so the schema documents query, include_gpu_breakdown and include_hardware_table. The description adds the headcount tiers (10/100/1,000/10,000) matching the enum and the industry concept, but leaves include_team and part of the boolean semantics unaddressed, giving it only baseline value.

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 (estimate) and resource (enterprise AI cost), and scopes it precisely: API (per-role model choice or open model's official API) vs self-hosting on public/private/on-prem GPUs, across 10/100/1,000/10,000-person company samples. It never names the overlapping sibling estimate_self_hosting, so an agent must still infer the boundary, but the purpose itself is unambiguous.

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?

Usage is only implied by the scope statement ('monthly AI cost for company samples across industries'). There is no explicit when-to-use, no when-not-to-use, and no routing to the closely related estimate_self_hosting or estimate_role_token_budget siblings.

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