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

No annotations, so the description carries the full behavioral burden. It usefully discloses the return shape (monthly cost plus a tier comparison table) and the input basis, but says nothing about whether this is a pure read-only computation, whether results are cached, or pricing-data freshness.

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 usage trigger followed by the input/output summary. Every clause earns its place with 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?

No output schema, but the description compensates by stating what is returned (monthly cost plus tier comparison table). All six parameters are schema-documented and the usage context is covered; only pricing-source/freshness caveats are absent, which is minor.

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 the schema already documents all six parameters including the include_comparison default. The description paraphrases tokens-per-call, call volume, provider/model, and the comparison table but adds no syntax, format, or default detail beyond the schema. Baseline 3 applies.

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+resource: computing LLM workload cost for a specific provider/model, with an explicit comparison mode. It partially differentiates from the crowded sibling set (all cost calculators) by naming 'provider/model' scope, but does not contrast itself against agent-loop-cost-calculator, eval-cost-calculator, etc.

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 clear triggering condition ('when a user asks what an LLM workload costs on a specific provider/model, or wants to compare cost across providers'). No when-not guidance and no named alternatives, but the trigger is unambiguous.

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