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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds useful behavioral context beyond that: data sources (S&P Capital IQ public aggregates and Damodaran), the user audience, and the $0.02 USDC per-call cost. It does not describe response format or data freshness, but the annotations lower the bar for this dimension.

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 front-loaded with the most actionable 'Use when' guidance and covers source, use case, and cost in a compact format. The sentence about CFOs and treasurers partially repeats the opening scenario list but still adds audience context. It is slightly longer than necessary but each major element earns its place.

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 there is no output schema, the description does a good job of stating what will be returned: Net Debt/EBITDA, interest coverage, and debt maturity profiles broken down by industry and credit rating tier. It also names sources and pricing. It does not specify exact response shape or data frequency, but for a benchmark lookup tool the coverage is largely 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 0%, so the description must compensate for parameter meaning. It does connect the two parameters to output dimensions by saying benchmarks are broken down 'by credit rating tier and industry,' and the schema's enums are fairly self-descriptive. However, it does not explain what each enum value represents, why credit_rating_tier is optional, or what happens when it is omitted.

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 purpose: assessing debt capacity, benchmarking leverage against sector peers, and preparing refinancing or credit rating discussions. It names specific outputs—Net Debt/EBITDA, interest coverage, and debt maturity profiles—which gives a concrete resource, though it does not explicitly differentiate from closely named siblings like get_cre_debt_benchmark or get_real_estate_debt_stress_benchmark.

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 opens with explicit 'Use when' guidance covering multiple relevant scenarios: debt capacity assessment, peer leverage benchmarking, refinancing, and credit rating discussion. It does not mention when not to use it or point to alternative tools, but the stated use cases are clear enough for an agent to decide when it applies.

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