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

No annotations are provided, so the description carries the burden. It discloses the computed outputs, including the non-obvious 'reading time', but does not state that the operation is pure/read-only and side-effect free, nor how reading time is derived (e.g., words-per-minute basis), which matters for interpreting results.

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?

One sentence, front-loaded with the verb and the full metric list, with zero filler. Everything in it is informative.

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 counting tool with no output schema, the description enumerates what comes back, which is what an agent needs to select and invoke it. A note on return shape or reading-time basis would close the remaining gap.

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?

There is a single required parameter 'text' with 100% schema description coverage ('Text to measure'), so the schema already does the work. The description adds nothing about input handling (size limits, formatting, encoding), leaving it at the baseline for a fully documented schema.

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?

States a specific verb (Count) and enumerates the exact resources measured (characters, words, sentences, paragraphs, lines, reading time). None of the sibling utilities (base64, hash_text, json_format, etc.) overlap, so an agent can distinguish it immediately.

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 strongly implied by the purpose — feed text, get metrics — and no sibling tool competes for this function. However, the description never states when to prefer it or any conditions/limits on use, so guidance is only inferred rather than explicit.

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