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

With no annotations, the description carries the full behavioral burden, and it does disclose meaningful traits: pricing derived from published per-million rates, automatic batch multiplier for volume estimates, model coverage scope, and the x402 payment terms ($0.001/call, USDC on eip155:8453). It still omits how current the price table is and any freshness/rate-limit caveats, but the paid-call disclosure is above baseline.

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?

Three compact fragments with no filler, and the core purpose is front-loaded ahead of the pricing/payment details. Every clause adds information an agent can act on.

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 4-parameter, no-output-schema calculation tool, the description covers what it computes, which models are supported (enum also in schema), and the cost of invoking it. Missing only output-shape/currency expectations and price-table freshness, which are minor for this tool class.

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% and all four parameters are documented there, so the baseline is 3. The description adds the pricing formula concept (tokens × per-million price) and the batch-multiplier behavior, but not per-parameter meaning beyond what the schema already states.

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 states a specific verb and resource — converting input/output token counts into LLM API cost — plus the concrete pricing basis (published per-million prices across 15 named providers). This is enough to distinguish it from the nearest sibling dev_token_estimator (which counts tokens) and from the other *_calculator tools.

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?

Use context is only implied: the mention of a batch multiplier for 'monthly estimates' suggests a projection use case, but there is no explicit when-to-use or when-not-to-use guidance and no pointer to the complementary token-estimation tool. Adequate but leaves routing inference to the agent.

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