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

Annotations already declare readOnlyHint, openWorldHint, and idempotentHint. The description adds useful context by disclosing use of Wayback Machine and Common Crawl public APIs, which implies external data dependencies and potential variability. This adds value beyond the annotations and does not contradict them.

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 three focused sentences: what it does, what it takes/returns, and when to use it. Every sentence contributes information with no fluff or repetition, and the most critical purpose is front-loaded.

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?

The description covers purpose, inputs, outputs, use cases, and data sources, giving a complete picture for an agent to select and invoke the tool. The rich schema and presence of an output schema reduce the need for more detail, and the description doesn't leave major gaps.

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 descriptions cover all 4 parameters with full detail (url, async, toDate, fromDate). The description only rephrases 'optional time range' without adding new semantic meaning or clarifying edge cases, so it meets the baseline without exceeding it.

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 clearly specifies the tool's function: 'Evaluates content evergreen potential for CMOs by analyzing historical traffic patterns and backlink authority.' It names a concrete output (evergreen score 0-100, traffic trend analysis, backlink profile), distinguishing it from sibling content tools like content_catalog or content_compare.

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?

The description states it is 'Ideal for content strategy planning, SEO optimization, and identifying high-value evergreen assets,' providing clear use-case context. However, it does not explicitly state when not to use it or name alternative tools, so it falls short of full guidance.

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