Server Quality Checklist

Tool Scores

• accrued_interestA
  3.5/5.0
  Behavior2/5

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

  The description states 'Deterministic' implying no side effects, but for a computation tool, that is baseline. It does not disclose edge cases, error handling, or behavior when inputs are invalid (e.g., negative notional, reversed dates). With no annotations, the description carries the full burden and falls short.

  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?

  Two sentences with no wasted words. The first sentence states the core purpose, the second adds format details. Highly efficient.

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

  Completeness3/5

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

  The description covers the input and formula but does not describe the return value (presumably a number, likely in the same currency as notional). For a tool without an output schema, this omission reduces completeness.

  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?

  With 83% schema description coverage, the schema already documents parameters. The description adds value by clarifying the formula (notional * rate * day-count fraction) and emphasizing that rate is a decimal, which reinforces the schema. This goes beyond the baseline of 3.

  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 clearly states the tool computes exact simple accrued interest using notional, rate, and day-count fraction between two dates. It distinguishes from sibling tools (day_count_fraction, list_conventions) by focusing on the full interest calculation rather than just the fraction or conventions.

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

  Usage Guidelines2/5

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

  No guidance on when to use this tool vs alternatives. It does not mention that day_count_fraction is for obtaining the fraction alone, nor does it specify any prerequisites or when not to use it.

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

• day_count_fractionA
  3.6/5.0
  Behavior3/5

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

  The description calls the tool 'exact' and 'deterministic', which covers behavioral traits well in the absence of annotations. However, it does not disclose what the output looks like (e.g., a floating-point number), nor does it mention any edge cases or error handling, leaving some behavioral details implicit.

  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 two sentences long and front-loads the core purpose. Every word is necessary; no filler or redundancy exists.

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

  Completeness2/5

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

  Given the tool has 4 parameters (including an optional boolean) and no output schema, the description is insufficiently complete. It does not explain the return format, precision, error behavior (e.g., invalid dates, start after end), or provide examples, leaving agents without enough context for correct usage.

  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 75%, and the description repeats information already in the schema (e.g., 'Dates are ISO YYYY-MM-DD'). It adds no new meaning beyond what the input schema provides, so the baseline score of 3 is appropriate.

  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 explicitly states the verb 'compute day-count fraction between two dates under a market convention', which is specific and unambiguous. The sibling tools 'accrued_interest' and 'list_conventions' are clearly distinct in purpose, so no confusion arises.

  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 advises against using a model to estimate the fraction ('Deterministic; do not estimate this with a model'), implying that this tool should be used for exact calculations. However, it does not explicitly state when to use this tool over alternatives, nor does it provide context about prerequisites or conditions.

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

• list_conventionsA
  3.9/5.0
  Behavior3/5

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

  No annotations are provided, so the description carries the full burden. It states the tool lists conventions, which is simple and transparent. However, it does not disclose any potential side effects, authentication needs, or rate limits, but for a read-only list tool this is minimally adequate.

  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?

  A single sentence that is concise and front-loaded. Every word is necessary and there is no superfluous information.

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

  Completeness5/5

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

  Given that the tool has no parameters, no output schema, and a simple purpose, the description is complete. It tells the agent exactly what the tool does without missing information.

  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?

  The tool has no parameters, and schema coverage is 100%. The description adds no parameter information, but with zero parameters, the baseline is 4. The description does not explain what conventions are or the output format, but the absence of parameters means no additional semantics are needed.

  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 clearly states the tool lists supported day-count conventions, with a specific verb ('list') and resource ('supported day-count conventions'). It distinguishes itself from sibling tools like 'accrued_interest' and 'day_count_fraction' which are computation tools, not listing tools.

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

  Usage Guidelines2/5

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

  The description provides no guidance on when to use this tool versus alternatives. There is no mention of when not to use it or any prerequisites, which is a gap given two sibling tools exist.

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