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

With annotations already declaring readOnlyHint=true, idempotentHint=true, and destructiveHint=false, the description adds valuable behavioral context beyond annotations. It details what the engine evaluates (7 ecosystems, 8 protocols, hub requirements, subscription cost stacking) and the output format (score and verdict), providing a clear picture of the tool's operation without contradicting 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 three sentences, immediately front-loading the main action. Each sentence adds value: it states what the tool does, details evaluation criteria and return format, and provides methodology reference. No fluff or redundancy; it's concise and well-structured.

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 tool's complexity (7 ecosystems, 8 protocols) and absence of an output schema, the description is remarkably complete. It explains what the tool evaluates, the return format (score and verdict), and where to find methodology details, enabling an agent to select and invoke it appropriately without additional documentation.

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?

The input schema has 100% coverage, with descriptions for existing_devices and candidate_product already specifying what values to provide. The description adds general context about the evaluation dimensions but does not provide new parameter-level semantics beyond the schema. Baseline 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 the tool's function: checking if a smart home device fits a user's existing setup using a specific compatibility engine. It uses a specific verb ('check') and resource (device compatibility), and distinguishes itself from siblings like compare_products and get_product_verdict by focusing on compatibility with existing devices, not general comparison or verdicts.

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 indicates when to use this tool (to evaluate device compatibility across multiple ecosystems) and emphasizes its uniqueness, suggesting it is the go-to for cross-ecosystem compatibility analysis. It does not explicitly name alternative tools or provide when-not-to-use guidance, but the clear use case and differentiation earn a 4.

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