get_follower_statistics

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

With no annotations provided, the description carries the transparency burden. It discloses the two behavioral modes and their outputs (demographic breakdowns vs organic/paid gains), which is valuable. However, it doesn't mention any permission requirements, rate limits, or potential errors, which would be expected for a complete behavioral picture. The description is moderately transparent but not exhaustive.

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 two sentences, front-loaded with the primary purpose in the first few words. It packs mode differentiation and output expectations into a compact space without redundancy. Every clause adds value, making it highly concise 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?

Given the tool's complexity (4 params, no output schema, no annotations), the description covers the essential behavioral modes and their outputs. It doesn't explicitly mention the organization_id parameter, but the schema covers that. The lack of output schema is partially compensated by describing the returned categories (seniority, function, industry, etc.). Still, a slightly richer description of the returned data structure would make it fully 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 schema provides 100% coverage of parameters, so the baseline is 3. The description adds semantic meaning by explaining how start_ms/end_ms and granularity relate to the two modes, e.g., 'Lifetime mode (omit start/end)' and 'Time-bound mode' returns gains per bucket. This goes beyond the individual parameter descriptions and helps the agent understand the interaction between parameters.

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 opens with 'Follower analytics for a Company Page', which clearly states the verb (analytics/get), resource (followers/Company Page), and scope. It distinguishes from sibling tools like get_page_statistics and get_share_statistics by focusing specifically on follower data. The two modes (lifetime and time-bound) further clarify what the tool does.

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 explicit guidance on when to use lifetime mode (omit start/end) versus time-bound mode, which is effectively a usage rule for parameter configuration. It does not explicitly name alternative tools, but the context of follower analytics and the mode descriptions give sufficient clarity for an agent to determine appropriate use.

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