Server Quality Checklist

Tool Scores

• noise_floorA
  4.7/5.0
  Behavior4/5

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

  With no annotations provided, the description carries full burden and does well by explaining key behaviors: it returns a PhysicalViolationError for thermodynamic limit violations, uses standard formulas (kTB, Friis), and provides default values. It could improve by mentioning computational complexity or precision limitations, but covers core behavioral aspects adequately.

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

  Conciseness4/5

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

  The description is well-structured with clear sections: purpose explanation, usage guidelines, error behavior, and parameter documentation. While slightly longer than minimal, every sentence adds value. It could be slightly more front-loaded by moving usage guidelines earlier, but overall efficient.

  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 the tool's complexity (multiple calculations, error conditions) and 0% schema coverage, the description is remarkably complete. It explains purpose, usage, behavior, and all parameters thoroughly. With an output schema present, it appropriately doesn't explain return values, focusing instead on what the tool does and how to use it.

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

  Parameters5/5

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

  With 0% schema description coverage, the description fully compensates by explaining all 4 parameters: bandwidth_hz (receiver bandwidth in Hz), temperature_k (system noise temperature with default 290K), stages (list with gain_db and noise_figure_db keys), and required_snr_db (required SNR for sensitivity). It adds essential meaning beyond the bare schema.

  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 tool calculates thermal noise power, cascaded noise figure, and receiver sensitivity with specific formulas (kTB, Friis formula). It clearly distinguishes from sibling tools like radar_range, rf_link_budget, and shannon_hartley by focusing on noise floor calculations rather than range, link budget, or channel capacity.

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

  Usage Guidelines5/5

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

  The description provides explicit bullet points for when to use this tool: determining thermal noise floor, cascading noise figures, calculating receiver sensitivity, and validating noise figure plausibility. This gives clear guidance on appropriate contexts and distinguishes it from alternatives.

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

• radar_rangeA
  4.7/5.0
  Behavior4/5

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

  With no annotations provided, the description carries full burden and does an excellent job disclosing behavioral traits. It explains the specific equation used, mentions error handling ('Returns a PhysicalViolationError dict if any input violates physics'), describes the return format ('Returns both human-readable summary and machine-readable JSON'), and warns about common misconceptions ('Catches the common fourth-root fallacy'). The only minor gap is not explicitly mentioning rate limits or authentication requirements.

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

  Conciseness4/5

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

  The description is well-structured and appropriately sized for a complex tool with 10 parameters. It front-loads the core purpose, then provides usage guidelines, return behavior, and detailed parameter explanations. While comprehensive, every sentence earns its place by adding necessary information for this technical domain tool.

  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 the tool's complexity (10 parameters, physics calculations), no annotations, but with an output schema, the description is remarkably complete. It covers purpose, usage scenarios, behavioral traits, parameter semantics, and return behavior. The output schema handles return values, so the description appropriately focuses on what the tool does rather than output structure.

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

  Parameters5/5

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

  With 0% schema description coverage and 10 parameters, the description provides comprehensive parameter semantics beyond the bare schema. It explains each parameter's meaning, units, constraints ('must be > 0'), and default values. The description fully compensates for the schema's lack of documentation, adding crucial context about physical meaning and validation requirements.

  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's purpose with specific verbs ('calculate', 'validate') and resources ('maximum monostatic radar detection range', 'range claims'). It explicitly distinguishes this tool from potential siblings by focusing on the radar range equation and validation, unlike tools like 'noise_floor' or 'shannon_hartley' which address different RF concepts.

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

  Usage Guidelines5/5

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

  The description provides explicit usage guidelines with a bulleted list of five specific scenarios when to use this tool ('Calculate the maximum detection range', 'Validate whether a claimed radar detection range is physically achievable', etc.). It also implicitly distinguishes from siblings by focusing on radar-specific calculations rather than general noise or link budget analysis.

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

• rf_link_budgetA
  4.8/5.0
  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 of behavioral disclosure and does so effectively. It explains the tool validates antenna gains against aperture limits, rejects physically impossible configurations, and returns specific error types (PhysicalViolationError). It also describes the dual output format (human-readable summary and machine-readable JSON). However, it doesn't mention rate limits, authentication needs, or potential side effects.

  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 well-structured and appropriately sized. It begins with the core purpose, then provides usage guidelines, return behavior, and detailed parameter documentation. Every sentence earns its place by adding specific value, with no redundant or vague content.

  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 the complexity of a 9-parameter RF calculation tool with no annotations, the description is remarkably complete. It explains the tool's purpose, when to use it, behavioral characteristics (validation, error handling), return formats, and detailed parameter semantics. With an output schema present, it appropriately doesn't need to explain return values in detail.

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

  Parameters5/5

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

  With 0% schema description coverage, the description fully compensates by providing detailed parameter documentation. Each of the 9 parameters is clearly explained with units, constraints (must be > 0 for frequency/distance), default values, and purpose (e.g., 'enables aperture check' for diameter parameters). This adds substantial meaning beyond the bare schema.

  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's purpose with specific verbs and resources: 'Calculate a complete RF link budget using the Friis transmission equation' and lists specific computations (FSPL, received power, antenna validation). It distinguishes from siblings by focusing on RF link budget calculations rather than noise analysis, radar range, or channel capacity.

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

  Usage Guidelines5/5

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

  The description provides explicit usage guidelines with a bulleted list of four specific scenarios when to use this tool: estimating received signal strength, validating link budget achievability, checking antenna gain consistency, and computing free-space path loss. This gives clear context for when this tool is appropriate versus alternatives.

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

• shannon_hartleyA
  4.8/5.0
  Behavior4/5

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

  With no annotations provided, the description carries full burden and does well by disclosing key behaviors: it explains the mathematical formula used, specifies that claims exceeding the Shannon limit are 'physical impossibility', and mentions the PhysicalViolationError return for invalid claims. It doesn't cover error handling for other cases or rate limits, but provides substantial behavioral context.

  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 well-structured and front-loaded with the core purpose, followed by usage guidelines and parameter explanations. Every sentence earns its place by providing essential information without redundancy, making it efficient for an AI agent to parse.

  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 the tool's mathematical nature, 4 parameters with 0% schema coverage, no annotations, but with an output schema mentioned, the description is complete. It explains the tool's purpose, usage, parameters, and even hints at output behavior (PhysicalViolationError), leaving the output schema to handle return value details.

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

  Parameters5/5

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

  With 0% schema description coverage, the description fully compensates by explaining all parameters: bandwidth_hz ('Channel bandwidth in Hz'), snr_linear and snr_db (clarifying linear vs dB units and their mutual exclusivity), and claimed_throughput_bps ('Optional throughput claim to validate'). It adds crucial meaning beyond the bare schema.

  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's purpose with specific verbs ('Calculate Shannon-Hartley channel capacity', 'validate throughput claims') and distinguishes it from sibling tools like 'noise_floor' or 'rf_link_budget' by focusing on channel capacity calculations rather than noise analysis or link budgeting.

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

  Usage Guidelines5/5

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

  The description provides explicit guidance on when to use this tool through a bulleted list ('Calculate maximum achievable throughput', 'Validate whether a throughput claim is physically possible', etc.), clearly differentiating its use cases from potential alternatives without needing to name specific siblings.

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