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

No annotations are provided, so the description carries the burden. It discloses the cost ($0.001 USDC) and the output dimensions (language, readability, etc.), which is useful. However, it does not mention potential side effects, errors, or return format. For an analysis tool, this is acceptable but not fully transparent.

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, efficient sentence that front-loads the purpose and includes the price. No wasted words; every element (languages, outputs, cost) 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?

For a tool with no output schema and no annotations, the description lists the outputs, supported languages, and price. It covers the essential information an agent needs to decide and invoke the tool. Missing details like error handling or async behavior are minor for a text analysis tool.

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 coverage is 100% (both parameters have descriptions). The description mentions 'keywords' and 'phrases' but does not add anything about the 'topN' parameter beyond what the schema already states. The description adds marginal value, so the baseline of 3 is appropriate.

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?

Description clearly states it analyzes text and lists specific outputs (language, readability, keywords, key phrases, sentiment, statistics), with a distinct resource ('text'). Sibling tools (extract_webpage, pricing, seo_audit) are obviously different in purpose, so it differentiates well.

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 description—it is for analyzing text—but it does not explicitly state when to choose this over alternatives or any exclusions. No mention of prerequisites or conditions. The sibling tools are different enough that an agent can infer, but there is no direct guidance.

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