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

With no annotations provided, the description carries the full burden of behavioral disclosure. It does not mention whether this is a read-only operation, whether date ranges are required or optional, how metrics are aggregated, what happens with invalid account_ids, or any pagination/response details. The description adds minimal behavioral context beyond the name and schema.

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 a single concise sentence that front-loads the core purpose and includes the key metric types. It is efficient and easy to parse, though it could add a bit more context without becoming bloated.

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?

Given the tool has 4 parameters, no output schema, no annotations, and 0% schema description coverage, the description is too thin. An agent would not know how to format dates, whether account_ids is required for filtering, what the response shape is, or how this differs from sibling metric tools. The description is adequate only for a very basic understanding.

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 for the four parameters. It mentions metrics and grouping by date, which loosely maps to the 'metrics' and date parameters, but it does not explain the format of date_from/date_to, the meaning of account_ids, or how the metrics parameter should be structured. The description adds some meaning but leaves most parameter semantics to be inferred.

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 specific verb ('Get') and resource ('post engagement metrics'), and lists the metric types (likes, comments, shares) and grouping by date. It is clear what the tool does, though it does not explicitly distinguish itself from the sibling get_account_metrics or get_engagement_trend, which are related but different resources.

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 about when to use this tool versus alternatives like get_account_metrics, get_engagement_trend, or get_stats_overview. The description implies it is for post-level metrics, but it does not state exclusions or conditions that would help an agent choose among the many metric-related siblings.

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