Audience demographics

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

Annotations already declare readOnly/idempotent/non-destructive, so they carry the safety profile; the description adds real behavioral context the annotations cannot — the 100-follower threshold and the live-account requirement, both of which determine whether the call succeeds. It stops short of documenting rate limits or what happens below the threshold (empty result vs error).

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?

Two sentences, no filler, and the resource definition is front-loaded ahead of the eligibility constraint and enum guidance. Every clause carries information an agent would otherwise have to guess.

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?

No output schema exists, so the description should ideally say something about the returned shape, and it does not — that is the main gap. Against that, it covers the resource, the eligibility precondition, and the primary enum semantics, which is close to what an agent needs given four short enum parameters.

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 only 25% (just response_format), so the description is doing meaningful work by defining the semantics of both 'followers' and 'engaged' and the available breakdown dimensions. But 'timeframe' is referenced only vaguely ('in the timeframe') and the accepted values/behavior of narrowing or widening the window are never explained.

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 first sentence names a specific resource (audience demographics of the account) and enumerates the breakdown dimensions, so an agent can tell this apart from ig_get_account_insights or ig_get_media_insights. It lacks an explicit verb ('Get'/'Retrieve'), but the resource and scope are unambiguous.

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 a concrete precondition ('Needs at least 100 followers on a live account') and disambiguates the 'followers' vs 'engaged' choice, which is genuine usage guidance. However, it never says when to prefer this over sibling analytics tools like ig_get_account_insights, nor any when-not conditions.

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