credit_model_summary

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

No annotations are provided, so the description must carry the burden of behavioral disclosure. It states the tool returns metadata but does not explicitly confirm it is read-only or non-destructive. Given the tool's nature, it is likely safe, but the description lacks explicit statements about side effects, authentication, or rate limits.

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 a single, well-structured sentence that front-loads the key concept ('Metadata for the credit scorecard') and then lists specific metrics. Every part adds value, and there is no redundancy or waste.

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 has zero parameters, no output schema, and no annotations, the description provides adequate context by listing the key output components (held-out AUROC/Gini/KS, per-feature IV, valid categorical inputs). It does not specify the output format, but the list is sufficient for an agent to understand what the tool returns.

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 has zero parameters, and schema coverage is 100% (trivially). With 0 parameters, the baseline is 4. The description does not need to add parameter details, but it implicitly explains the output content which is the tool's purpose.

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 provides metadata for a credit scorecard, listing specific metrics (AUROC, Gini, KS, Information Values) and valid categorical inputs. It uses a specific verb-resource combination and distinguishes itself from sibling tools which focus on risk measures and scoring.

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 implies usage context by naming the specific metrics, but does not explicitly state when to use this tool versus siblings like 'score_credit_application' or 'backtest_var'. No guidance on prerequisites or alternatives is provided, though the tool's self-contained nature (no parameters) reduces the need for extensive guidance.

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