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

Beyond the annotations (readOnlyHint, idempotentHint), the description discloses substantial behavioral details: merchant emails are dropped at the MCP boundary, authentication requires a Bearer JWT with a specific scope via a two-header model, and invalid/missing credentials degrade to an empty envelope. It also describes the output shape (rows with tier and 4 facets, plus a rollup aggregate). This goes far beyond what annotations provide.

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 four dense sentences, each carrying essential information: purpose, output, brand-exposure constraint, and authentication. It is front-loaded with purpose and avoids fluff, though it is slightly longer than minimal.

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 (nested criteria, no output schema), the description provides a good high-level picture: what it searches, what it returns, and how auth/errors behave. It does not detail the exact output schema or all parameter semantics, but it is complete enough for an agent to understand the tool's role and safety profile.

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 0%, so the description must compensate for parameters. It mentions 'credit tier' and 'ranking facet', which maps to criteria.tier and criteria.sortBy, but it uses different enum names ('sales-efficiency' vs 'efficiency', 'operational risk' vs 'risk') than the schema, which could confuse the agent. It also does not explain the nested criteria object structure, nor limit, order, windowDays, or agentBearer. The partial mapping is not enough to fully compensate.

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 ('Search') targeting a specific resource ('KYB-verified droplinked merchant cohort grid') with scoping criteria ('by credit tier and ranking facet'). It also distinguishes itself from sibling tools by its lender-agent use case and the unique cohort grid, making it clear what this tool does and how it differs from find_merchant or other search tools.

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 states when to use it: 'Used by lender-agents to answer which merchants match my underwriting box?' It also provides a when-not via the brand-exposure discipline, saying lenders should use the marketplace offer flow, not direct outreach. However, it does not name alternative sibling tools, so it falls short of a 5.

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