Advertiser analytics for your own X posts, over any date range

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

Annotations cover safety (readOnly, openWorld, non-destructive), but the description adds crucial operational details: 'COSTS CREDITS PER POST READ', 'Needs X connected', 'Takes up to 25 post ids at once', 'window actually queried is reported back'. It also explains that older posts return nothing rather than zero performance, which is a significant behavioral nuance.

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?

Every sentence contributes information: parity with sibling, use cases, limits, defaults, cost warning, and connectivity requirement. The description is front-loaded with the main purpose and uses capitalization for critical warnings, making it efficient and scannable.

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 tool with four parameters, full schema coverage, and no output schema, the description covers what metrics are returned, limits, default behavior, costs, prerequisites, and the distinction from the sibling. Nothing an agent needs to call it correctly is missing.

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?

Although schema coverage is 100%, the description adds value beyond the schema by clarifying the ids limit ('up to 25 post ids'), the default date window ('defaults to the last 28 days'), and the reporting of the actual queried window. It does not explicitly explain each parameter individually, but the added context is meaningful.

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 identifies the tool as advertiser-grade X analytics with a specific list of metrics, and explicitly states it covers 'any date range' distinguishing it from x_post_insights. The phrase 'This is the one to use for...' further clarifies its specific role.

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 explicit usage cases ('how did last week’s post do', 'compare these three posts over the month') and contrasts with the sibling tool: 'x_post_insights physically cannot see past yesterday'. It also specifies the alternative, providing clear when-to-use and when-not-to-use guidance.

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