Server Quality Checklist

Tool Scores

• create_mathematica_sessionA
  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 the full burden of behavioral disclosure. It effectively describes key traits: the session is 'isolated' and 'independent' with its own state, returns a 'unique, secure session identifier', and includes an example output. However, it lacks details on potential errors, session limits, or initialization time.

  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 context, behavioral details, and output example. Every sentence adds value without redundancy, making it efficient and easy 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 simplicity (0 parameters, no annotations, but with an output schema), the description is complete. It explains the purpose, usage workflow, behavioral isolation, and provides an output example, compensating adequately for the lack of annotations while leveraging the output schema for return value details.

  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 0 parameters with 100% schema description coverage, so the baseline is 4. The description adds no parameter-specific information (as none exist), which is appropriate and doesn't detract from the 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 specific action ('Creates and initializes') and resource ('new, isolated Wolfram Language session'), distinguishing it from siblings like 'close_mathematica_session' and 'execute_mathematica_code'. It explicitly defines this as the first step for Mathematica tasks, establishing its unique role.

  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 ('first step for any Mathematica-related task') and how it relates to alternatives ('MUST use in subsequent calls to 'execute_code' and 'close_session''). It clearly defines the workflow context without misleading exclusions.

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

• execute_mathematica_codeA
  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 session context persistence ('can access variables and functions defined in previous calls'), execution constraints ('code should be syntactically correct'), and return value variability. It doesn't mention potential errors, timeouts, or resource limits, keeping it from a perfect score.

  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?

  Well-structured with a clear opening sentence stating purpose, followed by usage guidelines, then detailed parameter explanations with examples, and finally return value information. Every sentence adds value with no 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 2-parameter tool with no annotations and no output schema, the description provides excellent coverage of purpose, usage, parameters, and return behavior. It could be slightly more complete by mentioning potential error cases or execution limits, but it's very thorough for the given context.

  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?

  Schema description coverage is 0%, so the description must compensate fully. It provides detailed semantics for both parameters: 'session_id' is explained as a unique identifier from 'create_session' with an example format, and 'code' is described with syntax requirements and three concrete examples showing different use cases.

  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 ('Executes a string of Wolfram Language code') and resource ('within a specific, active session'), distinguishing it from sibling tools like 'create_mathematica_session' and 'close_mathematica_session' which handle session lifecycle rather than code execution.

  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?

  Explicitly states when to use ('within a specific, active session') and prerequisites ('must provide a valid session_id obtained from a previous call to create_session'), and distinguishes from alternatives by specifying the session context requirement.

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

• close_mathematica_sessionA
  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: it discloses that the tool is destructive (terminates session, releases resources), has irreversible effects (ID becomes unusable), and has system-level implications (frees memory and licenses). It doesn't mention error handling or permissions, but covers core behavioral traits adequately for a termination tool.

  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?

  Perfectly structured and front-loaded: first sentence states core purpose, second provides usage guidance, third explains irreversible consequence. The Args/Returns sections are clearly labeled but not part of the description text being scored. Every sentence earns its place with no redundancy.

  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 1 parameter with 0% schema coverage and no annotations, the description provides complete context: purpose, usage guidelines, parameter semantics, and behavioral implications. The output schema exists, so return values needn't be explained in the description. This is comprehensive for a simple termination tool.

  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?

  Schema description coverage is 0%, so the description must compensate fully. It provides detailed semantics for the single parameter: explains what session_id represents ('unique identifier of the session'), constraints ('must be an ID from an active, open session'), and includes a concrete example ('bee-sloth-auk-mole'). This adds significant value 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 specific action ('Terminates a specific Wolfram Language session') and resource ('releases all associated resources'), distinguishing it from sibling tools like create_mathematica_session (creates) and execute_mathematica_code (runs code). The verb 'terminates' is precise and unambiguous.

  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?

  Explicitly states when to use ('when you are finished with a session to free up system memory and kernel licenses') and when not to use ('Once a session is closed, its ID can no longer be used'), with clear alternatives implied (use create_mathematica_session for new sessions or execute_mathematica_code for active ones). The guidance is practical and actionable.

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