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

The description discloses critical behavioral traits beyond the annotations: it explains that recommendations include sample counts, period-over-period percentages are based on raw totals, topPosts are grouped by platform, relativeToPlatformBest compares within the same platform only, and platform-specific metric limitations. This is substantial context not present in the annotations.

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 a single dense paragraph but efficiently packs in essential usage details without redundancy. It is front-loaded with the core purpose, then elaborates on data interpretation caveats, making it concise enough while maintaining completeness. Minor lack of formatting (e.g., bullet points) prevents a 5.

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?

Given the absence of an output schema, the description thoroughly explains the output contents, including metrics, comparisons, grouping, and platform-specific coverage. It even advises on interpreting statistics correctly, making it fully self-sufficient for an agent to understand what the tool returns and how to use it responsibly.

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 100%, with both parameters having clear descriptions. The tool description adds no new parameter semantics beyond restating defaults and the profile_ids scope, which is already in the schema. Baseline of 3 is appropriate.

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 what the tool does: it returns how published posts performed, including views, engagement, changes, best posting times, and top posts. It differentiates from siblings like account summary and billing summary by focusing specifically on post performance.

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 implies when to use the tool by detailing the data it provides, but does not explicitly contrast with alternative tools or state when not to use it. However, the context from the title and description makes the use case clear, and it advises on how to interpret the results, which is a form of guidance.

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