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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It only states the function and input types, with no mention of read-only behavior, output format, tokenizer specifics, or side effects. This is a notable gap for an agent deciding whether to invoke the tool.

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 a single, front-loaded sentence that states the core function with no redundant words. Every word adds value, and the sentence is compact yet clear.

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?

With no output schema and no annotations, the description must explain what the tool returns and any relevant constraints. It only states 'estimate token count', leaving the output shape (e.g., single number vs. per-text array) and tokenization behavior unspecified. This is incomplete for a tool that produces a quantitative result.

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%: both 'texts' and 'prompt' have descriptions. The description adds the 'or' relationship between the two parameters, but it does not clarify mutual exclusivity or behavior when both or neither are provided. Since the schema already documents each parameter, the description provides marginal added semantics, warranting the baseline score of 3.

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 ('Estimate') and clearly identifies the resource ('token count') and its input scope ('a prompt or batch of texts'). This distinct purpose is unambiguous and easily differentiated from siblings like analyze_prompt or optimize_prompt, which target other aspects of prompt handling.

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 implies usage when token estimation is needed, but it does not explicitly state when to use this tool over alternatives, nor does it mention any exclusions or prerequisites. Sibling tools exist but no cross-references or guidance is provided, so the context is only implicit.

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