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

Annotations already declare read-only, idempotent, non-destructive, closed-world behavior, so the description need not repeat safety details. The description adds valuable behavioral context: the exact metrics, engagement-rate definition, newest-first ordering, and per-platform grouping.

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?

Two tight sentences, front-loaded with the metrics and scope, then the single-post filter. Every phrase contributes useful information: metrics, engagement-rate meaning, grouping, time range, ordering, and post_id usage.

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?

For a simple read-only analytics query with full schema coverage, complete annotations, and no output schema, the description is complete enough. It lists the returned metrics, engagement-rate definition, grouping, ordering, and filtering behavior, leaving no major ambiguity for correct invocation.

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 100%, so the schema already documents days, limit, and post_id. The description adds a little meaning by noting the 1-to-365 day range and explaining that post_id limits results to one post, but it does not add information about limit or pagination 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 clearly states the specific metrics returned (views, likes, comments, shares, engagement rate), the grouping unit (each published post and platform), the time window, ordering, and the single-post filter. An agent can distinguish this per-post analytics tool from broader account analytics without opening the schema.

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?

It gives useful usage context: the last N days range and passing post_id for a single post. However, it does not explicitly compare this tool with siblings such as get_analytics, get_best_times, or get_link_clicks, so the agent must infer when to choose this per-post metrics view over alternatives.

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