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

There are no annotations, so the description carries the full burden, and it does add genuine behavioral context: 'High volume' signals scale expectations, the x402 note discloses a pay-per-use cost of 0.001 USDC on Base, and 'Estimate' frames the result as approximate. Yet it omits which tokenizer or tokenization standard the estimate uses, input-size limits, and what the response contains. With zero annotation coverage, these gaps are material.

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?

The description is compact and purpose-first: the verdict comes first, then a terse set of separate clauses for volume, input, and pricing. Each fragment earns its place, with the sole waste being 'input=text' which partially duplicates the schema. Overall, it is efficient, appropriately sized, and well organized.

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 single-parameter tool with no annotations and no output schema, the description covers the essentials: purpose, input, volume, and cost. However, it never says what the tool returns (a plain number? a breakdown?) or which tokenizer the estimate is based on, both relevant for the stated budgeting use case. Because there is no output schema to compensate, these omissions are noticeable.

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% — the only parameter has a description, 'texto a medir', so the schema already documents it. The description's 'input=text' merely restates what the schema conveys without adding tokenizer or format details. The baseline score of 3 applies because the description neither harms nor meaningfully enriches the parameter semantics.

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 action and resource: 'Estimate the token count of a text' is a clear verb+object pairing, and the parenthetical '(to budget LLM calls)' grounds the purpose. It naturally distinguishes itself from the many sibling text-processing tools because it is the only one dedicated to counting/estimation.

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 purpose clause 'to budget LLM calls' implies when the tool should be used, which provides some contextual guidance. However, the description never names alternatives, exclusions, or explicitly says when not to use it. For a tool with no obvious sibling competitor this is adequate, but it leaves the decision to inference.

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