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

No annotations present, so description must reveal behavior. It discloses return fields but does not mention rounding, thresholds, error handling, or that it uses UK official repayment rules. Lacks depth for a financial calculation tool.

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?

Two concise sentences: first clearly states purpose and output, second guides to related tools. No unnecessary words, perfectly front-loaded.

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?

Describes return object structure and points to related calculators. However, for a complex UK student loan calculation, missing details like plan-specific thresholds or repayment percentage logic. Could be more comprehensive.

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?

Input schema covers both parameters with descriptions. The description adds no additional parameter semantics beyond what schema already provides. Baseline score of 3 is appropriate due to 100% schema coverage.

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?

Description clearly states it calculates UK student loan repayments based on plan type and salary, and lists return fields. However, with siblings like 'calculate_student_loan_repayment' and 'calculate_us_student_loan', it could explicitly differentiate from the generic version.

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?

Provides basic input conditions (plan and salary) and mentions related tools via 'list_bundles'. No explicit when-to-use, when-not-to-use, or comparisons with other student loan tools. Adequate but limited guidance.

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