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

With no annotations provided, the description carries the full burden of behavioral disclosure. It only lists the output metrics, but does not reveal counting semantics (e.g., whether whitespace/newlines count as characters, how words are delimited). This lack of detail could lead to incorrect assumptions for edge cases.

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 extremely concise (four words), which is appropriate for a simple utility. It is front-loaded with the key output types. It does not waste words, though it could arguably include a brief note on counting conventions without sacrificing conciseness.

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?

The tool is simple (one parameter, no output schema), so the description need not be extensive. However, it is incomplete because it does not specify what constitutes a 'word' or 'line' and does not mention potential quirks (e.g., empty text handling). The absence of an output schema increases the need for the description to clarify return values, but the description provides only the metric names.

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% for the single 'text' parameter, whose description is 'Input text'. The tool description adds no further semantic meaning to the parameter, but since the schema already documents it thoroughly, a baseline of 3 is appropriate. The description does not introduce any ambiguity or extra constraints.

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 'Word, char, line counts' clearly identifies the tool's output as three counting metrics for text input. It is specific about the resource (text) and the type of computation, but lacks a verb, making it a noun phrase rather than an explicit action statement. It distinguishes from siblings like chunk_text or line_split by focusing on counts rather than transformations.

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?

Usage is implied by the tool name and description: when you need word, character, or line counts. No explicit guidance is provided about when to prefer this over similar text-analysis tools, nor exclusions or alternatives. The description gives no context about situations where this tool would be inappropriate or outperformed by a sibling.

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