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

Annotations already cover readOnlyHint=true and destructiveHint=false, so the safety profile is established. The description adds valuable behavioral context beyond annotations: the return fields (migration complexity, savings, narrative), the data source (Stratalize composite), and the cost per call ($0.10 USDC). It doesn't over-disclose or contradict 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 compact and well-ordered: a usage trigger, a summary of the return value, an illustrative example with concrete data, the data source, and the cost. Every sentence carries weight, and the example is informative without bloating the text. The structure is front-loaded with the most actionable instruction first.

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?

With no output schema, the description does the job of explaining what the agent will get: alternative vendors, migration complexity scores, savings, and switching narrative. The example provides realistic output shape (vendor names, percentages, complexity ratings). It lacks details about exact JSON structure or pagination, but for a read-only lookup with two well-documented parameters, this is sufficient.

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 100%, so the baseline is 3. The description doesn't add much beyond the schema's own parameter definitions: vendor_name and reason are already described as 'Incumbent vendor name' and 'Primary driver for evaluating alternatives.' The Salesforce example implicitly demonstrates usage but doesn't provide new semantic detail about parameter values or syntax.

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: 'Returns alternative vendors with migration complexity scores, estimated savings, and switching narrative.' The verb 'returns' plus the specific resource ('alternative vendors') and concrete output types distinguish it from sibling benchmarks and market rate tools. The Salesforce example solidifies the purpose with specific data points.

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 explicitly says 'Use when evaluating a vendor switch or building a competitive RFP against an incumbent,' giving clear invocation context. It doesn't name alternatives or exclusions, but the two use cases are specific enough to guide an agent. This meets 'clear context, no exclusions' rather than the full 5 needed for explicit when-not guidance.

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