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

With no annotations, the description carries the full burden and does supply useful traits — deterministic, read-only, no key needed — which tells an agent the call is safe, repeatable, and unauthenticated. It stops short of stating input-size limits (relevant given 'short post'), failure behavior, or latency/cost characteristics.

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 resource, then the return shape, then operational traits. Nothing is padded and nothing obvious is buried.

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 one-parameter tool with no output schema, the definition covers purpose, return shape (score plus plain-English suggestions), and operational profile (deterministic, read-only, no key). The remaining gap is input-length guidance, which matters for a tool scoped to 'short' text.

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 parameter with 100% schema coverage, so the baseline is high; the description still adds value by characterizing the input as a caption or short post rather than arbitrary text. The scope hint ('short') is useful but leaves exact length bounds unspecified.

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 pairs a specific verb with a specific resource — 'Score how human a caption or short post sounds' — and adds the output scale (0-100 plus suggestions). It is immediately distinguishable from the listed siblings (generation, status, pricing, ideas), though it never names an alternative itself.

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 phrasing: check a caption or short post for human-sounding quality. There is no explicit when-to-use, when-not-to-use, or comparison against a sibling, so an agent must infer the trigger condition from the purpose alone.

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