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

Annotations already cover read-only, non-destructive, non-idempotent, and open-world behavior, but the description adds meaningful context about pricing, the free quota, failed-call billing, and repeat charges. It also restates read-only behavior, though without contradicting the annotations.

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?

The description is a single front-loaded paragraph with no irrelevant sections. The pricing and billing sentence is dense but still earns its place by clarifying cost behavior.

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 two-parameter tool with full schema coverage and no output schema, the description supplies purpose, return ordering, use cases, and billing details. Nothing critical for correct invocation appears to be 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?

Schema description coverage is 100%, so both parameters are already well documented in the schema. The description does not add parameter-level meaning beyond the schema; 'most relevant first' describes return ordering rather than input semantics.

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 states the extracted resource (keywords and key phrases) and its ordering (most relevant first), and the title adds the explicit extraction verb. It does not clearly distinguish this tool from nearby siblings such as ai_extract_json or ai_summarize_text.

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 gives useful use cases (tagging, SEO, search indexing, topic detection) but does not say when to choose this over alternatives or when not to use it. Usage is implied rather than explicitly routed.

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