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

With no annotations, the description carries the full burden and does well: it discloses rate limiting (5 checks per caller per day), that no API key or auth is needed, the 5000-char input ceiling, and the shape of the response (0-100 score with located tells and fix hints). It stops short of stating failure modes or what happens when the quota is exhausted.

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?

Two sentences with zero filler, and the most decision-relevant facts (free, no key, quota) are front-loaded before the functional description. Every clause earns its place.

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, yet the description covers the essentials an agent needs: cost/auth, quota, input limit, and the return shape. Minor gaps remain around quota-exceeded behavior and latency, but nothing critical is missing for correct invocation.

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?

Only one parameter exists and the schema documents it at 100% coverage ('text to score (<= 5000 chars)'). The description repeats the same 5000-char constraint but adds no new syntax, format, or edge-case meaning beyond the schema, so the baseline 3 applies.

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 names a concrete verb and resource: 'score a text 0-100 for AI-writing tells', plus the output granularity ('each tell located with a fix hint'). That is far more specific than a tautology, though it never references any sibling tool to help an agent disambiguate within this large toolset.

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?

It implies when the tool applies ('score a text for AI-writing tells') but gives no explicit when-to-use/when-not guidance or named alternatives. The free/no-key/quota framing helps an agent decide it can afford to call it, but that is cost context rather than selection guidance.

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