get_account_analytics

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

With no annotations, the description carries the burden of disclosing behavior. It states that the result is a JSON string of aggregated metric totals and describes both parameters, which is useful. However, it does not clarify the meaning of the null default for metric_types, whether days_back is inclusive, or what happens on empty results.

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 compact and organized into Args and Returns sections. Every sentence contributes value, with the main purpose stated first and no filler or repetition.

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 two-optional-parameter analytics fetch, the description covers the key invocation details, and an output schema exists to cover return structure. The main gaps are edge-case semantics like null metric_types and time-window boundaries, but these are minor for typical agent use.

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 add meaning. It does this well by explaining metric_types with concrete examples and days_back with its meaning and default value. It falls short only by not stating behavior when metric_types is null or whether the list is exhaustive.

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 uses a specific verb ('Fetch') and clearly identifies the resource ('aggregated engagement metrics for the account') with a time-window scope. This distinguishes it from siblings like get_post_analytics, which operate at the post level. The purpose is immediately understandable.

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 clearly establishes the tool's context: account-level analytics over a specified time window, which guides an agent toward this tool when account-wide metrics are needed. It does not explicitly name alternatives or exclusions, but the account-versus-post distinction is evident from the phrasing.

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