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

The description goes well beyond the readOnly/idempotent annotations by disclosing that the score is weighted and composite, that sanctions hits zero the score regardless of other signals, and that the output includes an explainable evidence chain plus a list of sources that failed. This is substantive behavioral context an agent needs to interpret and trust the result.

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 dense but every sentence carries operational value: what the score means, which sources feed it, what the output includes, a critical exception rule, and when to use it. The structure front-loads the core function and then expands logically through inputs, behavior, and outputs.

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 present, the description appropriately enumerates the return fields: score, risk band, itemized evidence, sources queried, sources that failed, and a plain-text summary. Combined with the single parameter's full schema documentation and the explicit usage condition, the description is complete for correct invocation and interpretation.

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 already provides full coverage of the single parameter company_name, including examples and automatic normalization of common suffixes. The description does not need to add parameter detail and does not materially extend what the schema already states.

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 opens with a specific verb and resource: 'Compute a composite 0-100 Counterparty Risk Score for a company name.' It names the exact data sources involved and the output type, and it distinguishes the tool from the alternative of stitching five separate queries, making its purpose unmistakable among a large sibling set.

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 the tool: 'Use this when you need a single-call counterparty risk verdict instead of stitching five separate queries.' This gives the agent a clear decision rule and an implicit contrast with granular source-specific tools, even though those tools are not named individually.

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