get_followers

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It clearly explains the pagination behavior (index and count, default 24 max 24, increments by count), which is a key behavioral trait. It also lists return content. However, it does not mention error cases, rate limits, or authentication requirements, though for a read-only public endpoint this is not critical. Overall, it discloses the most relevant behaviors sufficiently.

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 concise and front-loaded with the core purpose. All sentences carry useful information: the first states the primary action, the second details return values, the third explains pagination and defaults, and the last gives a practical use case. No filler or redundancy, making it efficient and well-structured.

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 read-only list tool with no output schema, the description is complete enough. It explains what the tool returns (follower usernames, metadata, workbook details), how pagination works, and typical use cases. There is no output schema to delegate return-value explanation to, and the description covers that need. Minor omissions like error behavior are not essential for successful invocation and understanding.

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 0%, so the description must compensate. It does so admirably: it explains index and count semantics with a concrete example (0, 24, 48), states the default and max for count, and clearly indicates username as the target user. This goes beyond simple parameter names and gives the agent enough to invoke the tool correctly.

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 states the tool retrieves followers for a Tableau Public user, using a specific verb and resource. It distinguishes itself from the sibling 'get_following' by focusing on followers, and further details the return content (usernames, metadata, workbook details), making the purpose unmistakable.

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 provides a use case ('analyzing user communities and discovering related authors') which implies when to use the tool, but it does not explicitly compare against alternatives or state when not to use it. Sibling tools like get_following exist, and no exclusions or alternative guidance is given, so the usage context is only implied rather than explicit.

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