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

Annotations already establish this is a read-only, non-destructive, closed-world lookup, so the safety bar is met structurally. The description adds genuinely new behavior: the entry taxonomy, the fact that some entries are actionable via request_feature while platform rules are not, and the id linkage. It stops short of describing the shape of an entry beyond its conceptual fields, which costs it a point.

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 content is front-loaded: what the tool holds, then when to call it, then the follow-up path. Parenthetical examples aid comprehension rather than padding, though the second sentence packs multiple clauses together and could be split for faster scanning.

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?

With no output schema, the description carries the burden of explaining returns, and it does so at a conceptual level (what cannot be done, why, and what to do instead). An agent can call it correctly and interpret the result, though the concrete field names of an entry are only hinted at via 'limit_id'.

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 100% and both enum parameters are documented in the schema itself, so the baseline is 3. The description's 'Filter by platform or area' restates the schema without adding nuance — for example, it does not explain whether filters are combinable or what the default (no filter) returns.

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 names the exact resource and its three content categories — platform rules (with a concrete example: TikTok's API cannot delete a video), unbuilt features, and app-only features — so an agent knows precisely what a call returns. It is clearly distinct from sibling tools like check_media_compatibility or request_feature, which it explicitly routes to.

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?

It gives an explicit trigger ('Call it before you tell the user that OmniSocials cannot do something') plus a fallback condition ('when no other tool fits what the user asked'). It also names the follow-up alternative, request_feature with limit_id, and states the exclusion ('unless it is a platform rule'), leaving nothing to inference.

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