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

No annotations are provided, so the description carries the full behavioral burden. It mentions per-channel delivery state but does not disclose read-only nature, pagination, ordering, recency bounds, authentication requirements, or return structure.

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?

A single tight sentence with no wasted words. The key qualifiers—recent, brand-scoped, per-channel delivery state—are front-loaded and each earns its place.

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?

The tool is simple with one required parameter and no output schema, so the description is minimally viable. However, it omits important context for interpreting results, such as pagination limits, ordering of 'recent' posts, and the shape of per-channel delivery state.

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 implies the single parameter is a brand identifier via 'for a brand', but does not explain the expected ID format, where to obtain it, or any validation semantics.

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 identifies the resource ('posts') and scope ('recent posts for a brand') and hints at included data ('per-channel delivery state'). It is distinguishable from sibling mutation tools like create_post and cancel_post, though it does not use an explicit verb such as 'list'.

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 gives no explicit guidance on when to use this tool versus alternatives such as get_analytics or create_post. Usage is only implied by 'recent posts for a brand'; there are no exclusions or conditions.

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