Server Quality Checklist

Tool Scores

• calcslive_run_scriptB
  3.4/5.0
  Behavior3/5

  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 effectively describes key traits: 'stateless' (no persistence), 'automatically handles unit conversions, dependency graphs, and Greek letters' (functionality), and 'No article creation needed' (scope limitation). However, it lacks details on error handling, performance limits (e.g., computation time), or output format, which are important for a 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.

  Conciseness4/5

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

  The description is appropriately sized and front-loaded: the first sentence states the core purpose, followed by key features and an example. Each sentence adds value (e.g., explaining statelessness, automation features). It could be slightly more structured by separating usage notes from features, but it avoids redundancy and is 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?

  Given the complexity (3 parameters with nested objects, no output schema, no annotations), the description is moderately complete. It covers the tool's purpose, key behaviors, and provides an example, but lacks details on output format, error cases, or how it differs from siblings. For a stateless calculation tool with rich input schema, more contextual guidance would be beneficial.

  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 parameters thoroughly. The description adds some context by mentioning 'Define inputs and outputs as PQ objects' and providing an example, but it doesn't explain parameter semantics beyond what the schema provides (e.g., how 'pqs' array interacts with 'inputs'/'outputs' overrides). This meets the baseline for high schema coverage.

  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 clearly states the tool's purpose: 'Run stateless unit-aware calculations from Physical Quantity (PQ) script definitions.' It specifies the verb ('Run'), resource ('calculations'), and key characteristics ('stateless', 'unit-aware', 'from PQ script definitions'). However, it doesn't explicitly differentiate from sibling tools like 'calcslive_calculate' or 'calcslive_validate', which prevents a perfect score.

  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 implies usage context by stating 'No article creation needed - fully stateless' and providing an example, which suggests this tool is for one-off calculations. However, it doesn't explicitly state when to use this tool versus its siblings ('calcslive_calculate', 'calcslive_validate'), nor does it mention any prerequisites or exclusions. The guidance is present but not comprehensive.

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

• calcslive_calculateA
  4/5.0
  Behavior3/5

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

  With no annotations provided, the description carries the full burden. It discloses key behavioral traits: automatic unit conversions, dependency calculations, and the return format ('calculated outputs with values and units'). However, it doesn't mention error handling, performance characteristics, or authentication requirements that might be relevant for a calculation service.

  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 perfectly sized with three sentences that each earn their place: purpose statement, key capabilities, and concrete example with return format. It's front-loaded with the core functionality and wastes no words.

  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 calculation tool with 3 parameters, 100% schema coverage, and no output schema, the description provides good context about what the tool does and how it behaves. The main gap is the lack of output schema, which means the description doesn't detail the structure of returned results beyond mentioning 'values and units'.

  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%, providing comprehensive parameter documentation. The description adds minimal value beyond the schema - it mentions 'unit-aware engineering calculations' which aligns with the schema's unit handling, but doesn't provide additional syntax, format details, or constraints beyond what's already in the schema 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 clearly states the specific action ('Perform unit-aware engineering calculations'), the resource ('CalcsLive articles'), and distinguishes from siblings by focusing on calculation rather than validation or script execution. The hydro power example concretely illustrates the purpose.

  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 provides clear context for when to use this tool (engineering calculations with unit handling) and references a sibling tool ('calcslive_validate' for discovering articles). However, it doesn't explicitly state when NOT to use it or provide alternatives beyond the validation reference.

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

• calcslive_validateA
  4.2/5.0
  Behavior3/5

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

  With no annotations, the description carries the full burden. It describes the return content (metadata with PQs, descriptions, units) but lacks details on error handling, rate limits, or authentication needs. It adds some behavioral context but not comprehensively.

  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 main purpose, followed by usage context and return details in two efficient sentences. Every sentence adds value without 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?

  Given the simple single-parameter input and no output schema, the description adequately covers purpose, usage, and return format. However, as a tool with no annotations, it could benefit from more behavioral details like error cases or permissions.

  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 coverage is 100%, so the schema already documents the single parameter 'articleId' with description and type. The description adds no additional parameter semantics beyond implying it's used for validation, aligning with the baseline for high schema coverage.

  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 ('discover available inputs and outputs') and resource ('calculation article'), and distinguishes it from sibling tools by explicitly mentioning its preparatory role before 'calculate'.

  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?

  It provides explicit guidance on when to use this tool ('before calculate to understand what parameters are available') and names an alternative ('calculate'), making it clear this is for discovery rather than execution.

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