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

Annotations already declare readOnlyHint=true and destructiveHint=false, so safety is clear. The description adds valuable contextual behavior: it returns data from benchmark_cache when fresh, otherwise guidance to load intelligence in Stratalize, and it cites data sources (benchmark_cache + Stratalize composites). This goes beyond annotations to explain conditional/caching behavior, though it doesn't detail response format.

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 well-structured and appropriately sized. It opens with the use case, lists return fields, notes cache behavior, provides a concrete Salesforce example, and cites data sources—all in two sentences plus a source line. Every sentence earns its place with no redundant wording.

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 simplicity (2 params, 1 required), annotations covering read-only safety, and no output schema, the description is complete. It explains the purpose, the key return fields, data freshness behavior, source, and an illustrative example. No critical contextual information is missing for an agent to select and invoke the tool correctly.

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 both parameters (vendor_name and mcp_client_source) are fully documented in the schema. The description reinforces vendor_name with an example and clarifies the output context, but it doesn't add new parameter-level semantics beyond what the schema provides, so baseline 3 applies.

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 a specific verb+resource ('get vendor benchmark') and defines its purpose: providing org-specific vendor pricing vs market for CFOs/procurement leads before renewal or negotiation. It lists concrete return fields (market_low, market_median, etc.) and differentiates from sibling tools like get_vendor_market_rate by emphasizing the org-specific and negotiation context.

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 explicitly says when to use the tool ('when a CFO or procurement lead needs org-specific vendor pricing vs market before renewal or negotiation'), giving clear context. However, it does not mention when not to use it or name specific alternatives, so it stops short of full exclusion guidance.

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