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

It provides operational context by stating the tool runs 'straight away' because the server marks it read-only, adding value beyond the simple `readOnlyHint` annotation. It also documents the specific recommendation branching logic that occurs post-execution.

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 dense but efficient. The core purpose is front-loaded, and subsequent sentences incrementally add crucial information (workflow sequence, logic, environment) without wasted words.

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?

While there is no output schema, the tool's functional completeness is achieved through the detailed workflow and recommendation rules provided. It tells the AI exactly how to use this tool in a sequence of operations.

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?

With 100% schema coverage, the baseline is high. The description adds specific guidance on the `include_available_types` parameter, clarifying that it 'must' be true when evaluating schema recommendations.

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 tool clearly states its purpose is to retrieve schema markup attached to a post and check available schema types. It successfully differentiates itself by focusing on 'schema markup' rather than general post meta, contrasting it with siblings.

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 provides explicit usage instructions, specifically advising agents to use it after checking `rank-math/get-post-seo-meta`. It also details complex conditional logic regarding recommendation failures and upgrade messages.

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