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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering safety. The description adds valuable behavioral context by stating it returns separate counts and highlights the 'without guessing' aspect, which informs the agent about the tool's output style and reliability.

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 two sentences, front-loaded with the main action and results, followed by concrete, useful examples. Every word earns its place without unnecessary filler or repetition of schema details.

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 simple single-parameter tool with strong annotations and an output schema, the description fully covers purpose, behavior, and use cases. It provides enough context for an agent to select and invoke this tool correctly without ambiguity.

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?

The input schema is fully self-descriptive with 100% coverage: the single parameter 'text' is documented with its type and maxLength. The description adds no additional parameter-level detail beyond what the schema already provides, so the baseline of 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 uses a specific verb and resource: 'Count characters in text, with and without spaces.' It clearly distinguishes itself from sibling tools like word-counter and vowel-counter by emphasizing the two distinct outputs (with/without spaces) and the use case for character-limit checks.

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 gives clear context for when to use the tool, such as checking if text fits in a tweet (280 chars) or SMS (160 chars). It does not explicitly mention when not to use it or name alternatives, but the examples make the intended usage highly apparent.

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