Server Quality Checklist

Tool Scores

• compare_federal_student_loan_repayment_plansA
  4/5.0
  Behavior4/5

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

  With no annotations provided, the description carries the full burden, and it does so by explaining that it compares only eligible plans, returns excluded plans with the rule that excludes them, and is computed by a parity-verified engine rather than estimated. It does not describe the exact output shape, but the behavioral detail is substantial.

  Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

  Conciseness5/5

  Is the description appropriately sized, front-loaded, and free of redundancy?

  The description is front-loaded with the action, the list of plans, and the outputs, followed by reliability and usage guidance. Every sentence contributes necessary context, and there is no redundant filler or vague marketing language.

  Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

  Completeness4/5

  Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

  The tool has seven parameters and no output schema or annotations, so the description must explain what comes back; it does, listing monthly payment, lifetime cost, excluded plans, and the eligibility rule. Minor details such as exact output formatting or underlying assumed loan terms are absent, but they are not essential for correct invocation.

  Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

  Parameters3/5

  Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

  Schema description coverage is 100%, so the schema already documents all seven parameters. The description reinforces that loanType drives eligibility with a Parent PLUS and consolidation example, but that example already appears in the schema's loanType description, so it adds no new parameter meaning.

  Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

  Purpose4/5

  Does the description clearly state what the tool does and how it differs from similar tools?

  The description states a specific verb ('Compares') and resource ('US federal student loan across every repayment plan'), enumerates the eligible plans, and specifies what is returned. It does not explicitly differentiate from sibling tools by name, but its scope is unambiguous.

  Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

  Usage Guidelines4/5

  Does the description explain when to use this tool, when not to, or what alternatives exist?

  The description gives clear usage context: 'Use this instead of calculating federal repayment math yourself' and explains why eligibility is easy to get wrong. It does not mention sibling alternatives or say when not to use the tool, so it stops short of full when/when-not guidance.

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

• compare_married_filing_jointly_vs_separately_student_loansA
  4.4/5.0
  Behavior5/5

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

  With no annotations provided, the description must carry the full burden and does so excellently. It clearly warns that the tool models only the loan side, omits tax costs that can reverse the answer, and explicitly states that this limitation appears in the tool's output. It also discloses the output is a side-by-side comparison with monthly and lifetime differences.

  Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

  Conciseness5/5

  Is the description appropriately sized, front-loaded, and free of redundancy?

  The description is four sentences long and front-loaded with the core purpose. Every sentence earns its place: the scenario and outcomes, the return summary, the essential tax caveat, and an explicit usage rule. There is no filler or redundancy.

  Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

  Completeness4/5

  Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

  For a six-parameter calculator with no output schema, the description provides the necessary decision context: married/IDR eligibility, the two filing statuses, the monthly and lifetime outputs, and a built-in disclaimer. However, it does not specify the exact output shape or assumptions about which IDR plan applies, leaving minor gaps.

  Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

  Parameters3/5

  Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

  The schema descriptions already cover 100% of parameters with detailed entries, so the baseline is 3. The tool description adds general context by explaining the role of spouse income in the filing decision, which slightly reinforces the meaning of spouseAgi, but it does not add unique meaning for balance, ratePct, loanType, or dependents.

  Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

  Purpose5/5

  Does the description clearly state what the tool does and how it differs from similar tools?

  The description uses the specific verb 'prices' and clearly identifies the resource: the married filing-jointly vs separately decision under an income-driven federal student loan plan. It explains the comparison and result (monthly and lifetime cost difference), and the context distinguishes it from the sibling tools that focus on plan choice or RAP payment estimation.

  Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

  Usage Guidelines4/5

  Does the description explain when to use this tool, when not to, or what alternatives exist?

  The description gives explicit context for when to use this tool ('For a MARRIED borrower on an income-driven federal student loan plan') and directs the agent to 'Use it whenever a married borrower asks about IDR, RAP, PSLF or how to file.' It does not name alternative tools or provide a when-not-to-use statement, and the broad 'asks about IDR' phrase could invite overuse, so it is strong but not top-scoring.

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

• estimate_rap_monthly_paymentA
  4.4/5.0
  Behavior5/5

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

  With no annotations provided, the description carries the full burden of behavioral disclosure. It explains the sliding 1%–10% scale, the $50 dependent deduction, the $10 minimum, and warns that assuming zero income returns the $10 floor and looks like a real answer. This is rich, honest behavioral context that prevents misuse.

  Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

  Conciseness5/5

  Is the description appropriately sized, front-loaded, and free of redundancy?

  Three sentences, each earning its place: the first defines the tool's purpose, the second explains the underlying calculation logic and pitfalls, and the third gives the critical usage instruction. No filler or redundancy.

  Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

  Completeness4/5

  Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

  The description provides all necessary input-handling guidance and behavioral warnings for a calculation tool. Since there is no output schema, it does not describe the return format or units, but for a simple monthly payment estimate the output is reasonably inferable, and the calculation method is fully specified.

  Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

  Parameters4/5

  Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

  Schema coverage is 100%, so all parameters are documented in the schema. The description goes further by emphasizing that annualIncome must be actively requested and never defaulted, and by explaining the consequence of a zero value. This adds meaning beyond the schema's field-level descriptions.

  Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

  Purpose5/5

  Does the description clearly state what the tool does and how it differs from similar tools?

  The description states a specific verb ('Calculates') and resource ('the monthly payment under RAP'), and clarifies exactly what RAP is, distinguishing it from older IDR rules. This clearly differentiates it from the sibling comparison tools, which focus on comparing plans rather than estimating a payment.

  Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

  Usage Guidelines3/5

  Does the description explain when to use this tool, when not to, or what alternatives exist?

  The description gives an explicit prerequisite ('Requires the borrower's annual AGI') and instructs the agent to ask rather than assume, which is practical guidance. However, it does not explicitly state when to choose this tool over the sibling comparison tools, leaving that routing decision implicit.

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