Server Quality Checklist

Tool Scores

• Workload AnalysisC
  2.6/5.0
  Behavior2/5

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

  No annotations are provided, so the description carries full burden. While 'analysis' suggests a read operation, it doesn't clarify whether this tool makes changes, requires specific permissions, has rate limits, or what format results take. 'Proactive insights and predictive recommendations' hints at computational complexity but lacks concrete behavioral details needed for safe invocation.

  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 a single, efficient sentence that gets straight to the point without unnecessary words. While it could be more informative, every word contributes to describing the tool's function. The structure is appropriately front-loaded with the core purpose.

  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?

  For a tool with no annotations, no output schema, and sibling tools present, the description is insufficiently complete. It doesn't explain what 'workload' encompasses, what format results take, or how this differs from sibling tools. The agent lacks necessary context to use this tool effectively versus alternatives.

  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% with only one parameter ('assignee') clearly documented in the schema. The description adds no additional parameter information beyond what the schema already provides. With high schema coverage and minimal parameters, the baseline score of 3 is appropriate - the description doesn't compensate but doesn't need to given the schema's completeness.

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

  Purpose3/5

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

  The description states the tool performs 'workload analysis' with 'insights and recommendations', which gives a general purpose but lacks specificity about what resources or data it analyzes. It doesn't clearly distinguish from sibling tools like 'Risk Assessment' or 'Natural Language Query' - all could potentially analyze workload data. The description is somewhat vague rather than tautological.

  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 is provided about when to use this tool versus alternatives. The description doesn't mention prerequisites, appropriate contexts, or exclusions. With sibling tools like 'Risk Assessment' and 'Natural Language Query' available, the agent receives no help in choosing between them for workload-related tasks.

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

• Natural Language QueryC
  2.9/5.0
  Behavior2/5

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

  No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions 'enhanced entity discovery and intelligent analysis,' which hints at processing capabilities, but fails to describe key behavioral traits such as whether it's read-only or mutative, authentication needs, rate limits, or what the output looks like (e.g., structured data, analysis results). This leaves significant gaps for an agent to understand how the tool behaves.

  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 a single, efficient sentence: 'Process natural language queries with enhanced entity discovery and intelligent analysis.' It is front-loaded with the core purpose and includes no unnecessary words, making it highly concise and well-structured for quick understanding.

  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 complexity implied by 'enhanced entity discovery and intelligent analysis,' the lack of annotations, and no output schema, the description is incomplete. It doesn't explain what the tool returns (e.g., analysis results, entities discovered), behavioral constraints, or how it integrates with sibling tools. This leaves the agent with insufficient context for effective use.

  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 input schema has 100% description coverage, with the 'prompt' parameter clearly documented as a natural language query with length constraints. The description adds minimal value beyond this, as it doesn't provide additional context like examples of effective prompts or semantic nuances. With high schema coverage, the baseline score of 3 is appropriate, as the schema does the heavy lifting.

  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: 'Process natural language queries with enhanced entity discovery and intelligent analysis.' It specifies the verb ('process') and resource ('natural language queries'), and mentions key capabilities ('entity discovery', 'intelligent analysis'). However, it doesn't explicitly differentiate from sibling tools like 'Risk Assessment' or 'Workload Analysis' in terms of when to use each, 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 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 the sibling tools ('Risk Assessment' and 'Workload Analysis'). It doesn't specify contexts, exclusions, or alternatives. The only implied usage is for natural language queries, but this is too vague for effective tool selection among siblings.

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

• Risk AssessmentC
  2.9/5.0
  Behavior2/5

  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 mentions 'comprehensive' assessment with 'pattern detection and predictive analytics', which hints at analysis capabilities, but doesn't disclose critical behavioral traits like whether this is a read-only operation, if it requires specific permissions, what the output format might be, or any rate limits. The description is too vague about actual behavior.

  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 a single, efficient sentence that gets straight to the point without unnecessary words. It's appropriately sized for a tool with one parameter, though it could be slightly more structured by separating core function from additional features.

  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 complexity implied by 'comprehensive risk assessment' with analytics, no annotations, and no output schema, the description is incomplete. It doesn't explain what 'comprehensive' entails, what kind of risks are assessed, how results are returned, or any dependencies. For a tool that likely produces detailed analysis, this leaves significant gaps for an AI agent.

  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 description coverage is 100%, with the single parameter 'projectId' well-documented in the schema. The description doesn't add any meaningful parameter semantics beyond what the schema already provides (e.g., it doesn't explain how the projectId influences the risk assessment or what formats are expected). Baseline 3 is appropriate when the schema does the heavy lifting.

  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 performs 'comprehensive project risk assessment' with 'pattern detection and predictive analytics', specifying both the verb (assessment) and resource (project risk). However, it doesn't explicitly distinguish this from sibling tools like 'Natural Language Query' or 'Workload Analysis', which might also involve analysis functions.

  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 the sibling tools. It doesn't mention any prerequisites, alternatives, or specific contexts where this tool is preferred over others like 'Workload Analysis' for risk-related tasks.

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