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

Annotations already declare readOnly/idempotent/non-destructive/closed-world, so the safety profile is covered. The description adds two facts not in the annotations: no account is required, and it cannot buy credits (only a human can, via the web app) — a boundary that prevents a failed purchase attempt. Minor remaining gap is any note on result freshness, but nothing material is withheld.

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?

Three tight sentences: what it returns, when to use it versus the sibling, then the access and no-purchase caveats. The routing information is front-loaded and no sentence is filler.

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?

With no parameters and no output schema, the description carries the return-shape burden and does so in prose — credit unit value, word-count tiering, credit packs. Access requirements and the purchasing limitation are also covered, leaving nothing an agent needs before calling it.

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?

The tool takes zero parameters, so the baseline is 4. The description correctly says nothing about inputs and instead spends its space on what comes back, which is the right allocation.

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?

A specific verb plus resource ('Returns the public price list') followed by the exact contents: credit value in USD, word-count tiering of the package price, and purchasable credit packs. It explicitly contrasts with the sibling qualitative_quote_analysis, so an agent can separate the two without opening a schema.

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?

Gives the selecting condition directly: 'general pricing questions that have no concrete inputs', and names the alternative with its own condition ('exact price of a specific analysis' -> qualitative_quote_analysis). Both when-to-use and when-not-to-use are stated.

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