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

With no annotations, the description carries the full burden, but it only adds billing information ('1 Credits') and the vague claim of returning 'all people.' It does not disclose pagination behavior, response shape, required authorization, or whether 'all people' is truly unpaginated given the presence of a 'start' parameter.

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 short and front-loaded, with the core purpose in the first sentence. The billing and group metadata are compact and add some operational context, though the overall content is thin.

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 two-parameter list endpoint with no output schema and no annotations, the description is under-specified. It omits pagination semantics, parameter roles, and any details about the returned data, making it insufficient for reliable tool invocation.

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%, and the description does not explain either parameter. 'urn' is not identified as the post identifier, and 'start' is not explained as a pagination offset, leaving the agent to guess from examples alone.

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 clear action and resource: 'get all people that reacted a post,' which aligns with the title 'Post's likes.' It is distinguishable from sibling tools like get_api_v1_comments_likes by the resource type (post vs comment), though it does not explicitly differentiate itself.

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?

No guidance is provided on when to use this tool versus alternatives. The 'Group: Posts' label gives weak contextual placement, but there are no explicit use cases, prerequisites, or exclusions.

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