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

Annotations already declare readOnlyHint=true, so the read-only nature is covered. The description adds valuable behavioral detail: it discloses that engagement is not collected for LinkedIn/Threads/TikTok and that those platforms return publish status+URL instead. This goes beyond annotations and sets accurate expectations about the data completeness. No contradictions.

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 two sentences, front-loaded with the action and resource, then adds platform-specific details. Every sentence earns its place; there is no fluff or repetition of schema or annotation information.

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 (one parameter, output schema exists), and the description covers the purpose, scope, and platform-specific return behavior. With the output schema providing return structure, nothing critical is missing for an agent to call it correctly. It explains the main nuance (which platforms have metrics) clearly.

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 coverage is 0%, so the description must compensate. It adds meaning by specifying that the postId must refer to a published post that was sent to platforms, and it explains the outcome for different platforms. However, it does not elaborate on how to obtain the postId, format constraints, or error cases. It provides some semantic value but not enough to fully cover the parameter.

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 states the verb ('Fetch'), the resource ('engagement metrics for a published post'), and the scope ('across every platform it was sent to'). It distinguishes itself from siblings like get_post (which likely returns general post data) and get_publish_status (which focuses on status) by specifying the metric types and platform coverage. No ambiguity.

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 provides clear context on when to use the tool: when you need engagement metrics for a specific post across platforms. It also explains platform-specific behavior (Twitter/Instagram return metrics, others return only status+URL), which helps an agent decide if this tool meets its needs. However, it does not explicitly name alternatives or state when not to use it, so it falls short of a 5.

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