get_analytics_authors

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

With no annotations provided, the description must disclose behavioral traits on its own. It mentions the returned metrics but does not state that the operation is read-only, that results are sorted by 'top', or how the days and limit parameters affect behavior, which is a gap in transparency.

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 concise sentence that gets directly to the point without unnecessary filler. It is appropriately sized for the tool's simplicity.

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 absence of an output schema places more responsibility on the description to explain returns; while it gives examples ('views and visitors'), it lacks specificity about ordering, default limit, or the exact output structure. It also does not reference sibling tools, so context is only partially complete.

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 input schema already fully documents both parameters (days and limit) with descriptions and defaults, so the description adds no extra parameter-level meaning. The baseline of 3 applies because schema coverage is 100%.

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 a specific action ('Get analytics data') applied to a defined resource ('top authors from Parse.ly'), and includes result details ('metrics like views and visitors by author'). This clearly distinguishes it from sibling tools focused on posts or tags.

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 implies use for author-level analytics but does not explicitly state when to use it versus sibling tools like get_analytics_posts or get_analytics_tags. No exclusions or alternatives are mentioned, leaving usage guidance implicit.

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