metricool_get_best_time

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 does add one useful behavioral fact — results derive from historical engagement data, implying sparse or empty output for new/low-activity brands — but it never states that this is a read-only operation or whether a minimum data history is required.

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, front-loaded sentence with zero filler; the purpose and its basis are stated up front. It is appropriately sized for a one-parameter retrieval tool.

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 would ideally sketch the return shape (e.g., a ranked list of time slots) and note the LinkedIn-only scope, since there is no platform parameter to make that explicit at call time. It is adequate for a simple read but leaves these gaps.

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?

Only one parameter (brandId) and schema description coverage is 100%, so the schema already documents it fully. The description adds no syntax, format, or lookup guidance for brandId beyond what the schema provides, matching the baseline-3 rule for high-coverage schemas.

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?

States a specific verb ('Get') and resource ('optimal posting times') and scopes it to LinkedIn with a rationale (historical audience engagement patterns). This distinguishes it from the generic metricool_get_analytics and the scheduling siblings, though it never names them explicitly.

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 on when to use this versus metricool_get_analytics or how it relates to metricool_schedule_post. The agent must infer that this is a pre-scheduling recommendation step purely from the tool name.

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