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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and openWorldHint=false, so the safety profile is covered. The description adds that it works across platforms and accepts either engagement counts or base metrics, but it never says whether the result is a percentage or ratio, how missing metrics are treated, or what the `posts` parameter does to the calculation.

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 no filler; the platform list and metric/base lists each carry information. It is efficient, though the two parallel enumerations pack a lot into one clause and could be split for scannability.

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 7-parameter calculator with no output schema and read-only annotations, an agent has enough to make a correct call on the main path (supply counts plus base_value and base_type). What's missing is the `posts` parameter's role and the output unit, which for a metric calculator is a meaningful gap.

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 only 43%, and the bare schema leaves likes, comments, shares and saves entirely undocumented. The description compensates partially by naming those four metrics and the four base types, which is real added meaning over the enum alone. However, it never explains the aggregation rule (sum vs. average), omits the `posts` parameter that the schema describes as 'number of posts the totals cover', and gives no unit guidance for the output.

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 (calculates) and resource (engagement rate) plus the platforms and input metrics it covers, so the tool is immediately identifiable. It does not explicitly distinguish itself from numerically adjacent siblings like growth_rate or roas_check, but the noun 'engagement rate' is distinct enough that an agent won't confuse them.

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?

Usage is only implied: an agent infers you call this when you have raw like/comment/share/save counts and a follower/reach/impression/view denominator. There is no explicit when-to-use statement, no prerequisites, and no named alternative for related needs.

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