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

The description goes well beyond the readOnlyHint annotation: it explains that unsupported metrics appear as zero, that linkClicks are computed by BulkPublish and may be present even when platforms report no metrics, that bot traffic and link-preview traffic are excluded, and that organizations without Link Tracking see zero. This prevents common misinterpretations that annotations alone would not.

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 long but information-dense and front-loaded with the core purpose. The detailed per-platform metric notes and the zero-value warning are essential for correct use, though some redundancy exists around linkClicks being included in totals. Overall, each section 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 description covers the full semantics an agent needs: what metrics exist, which platforms report which metrics, how missing values are represented, how linkClicks differ from platform clicks, exclusions for bot traffic, and the exact user-request scenario that should trigger this tool. This is especially valuable given the rich output schema and potentially confusing zero values.

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?

The only parameter is postId, which the schema already documents. The description adds only that the post should be published and that the tool answers questions about a specific post's performance, which is minor extra context. It does not explain postId format, lookup semantics, or errors, so it provides little beyond the schema.

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 opens with a clear verb and resource: 'Get engagement metrics for a specific post.' It explicitly names the returned data (likes, comments, shares, views) and closes with an explicit use case. This distinguishes it from siblings like get_analytics or list_posts by fixing scope to a single post.

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 an explicit trigger: 'Use this when the user asks how a specific post performed.' It does not explicitly name alternative tools such as get_analytics or view_analytics for aggregate/cross-post analytics, so it misses the top bar for exclusion guidance. Still, the context for when this tool is appropriate is clear.

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