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

With no annotations, the description carries the full burden, and it does disclose the output dimensions (counts, reading time, Flesch score), which is genuinely useful behavioral information. However, it omits whether the computation is local/pure, whether the Flesch score assumes English text, or any length limits — meaningful gaps for a no-annotation 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?

A single front-loaded sentence with the resource named first and the outputs enumerated compactly; nothing is redundant. It is dense without being cryptic, though the list-heavy fragment style leaves little room for structure.

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?

There is no output schema and no annotations, so the description usefully compensates by enumerating the returned stats. Given the trivial single-parameter input, what an agent needs to invoke it correctly is essentially covered; only language/edge-case caveats are missing.

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?

One parameter with 0% schema description coverage, so the description must compensate; it only implicitly identifies the input as text and adds no constraints such as maximum length, language, or encoding. The parameter name is self-evident, keeping this at a minimum-viable level.

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 resource (text) and enumerates exactly what is computed: character/word/sentence counts, reading time, and Flesch reading-ease. This clearly separates it from siblings like summarize_text or encode_text. It stops short of naming an alternative, so it is clear but not sibling-differentiating.

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 only implied: an agent can infer you call this when you want metrics rather than a summary, but there is no explicit statement of when to use this versus summarize_text or what conditions make it appropriate. No prerequisites or exclusions are given.

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