Server Quality Checklist

Tool Scores

• search_dental_topicsB
  3.3/5.0
  Behavior2/5

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

  No annotations; description only says 'search for information' without disclosing read-only nature, rate limits, or scope of results.

  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?

  Concise with clear opening sentence and bullet-like examples. Could be more structured with explicit sections.

  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?

  Adequate for a simple lookup tool with output schema present, but does not describe the form of returned 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?

  Adds value over schema by providing concrete examples of valid topics (e.g., root canal, whitening), though no format or enum constraints.

  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?

  Clearly states 'Search for information about common dental topics' with examples. Differentiates from siblings implicitly but not explicitly.

  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?

  Implies usage for understanding patient questions but no explicit when-to-use or alternatives compared to siblings like ask_ravira.

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

• ask_raviraA
  3.6/5.0
  Behavior2/5

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

  No annotations provided, so the description carries full burden. It mentions that the tool 'demonstrates how Ravira handles real patient inquiries' but does not disclose behavioral traits such as response latency, auth requirements, or whether the AI is simulated. The return value is vaguely described as 'the AI receptionist's response'.

  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 a brief statement, a sentence on scope, and an Args block. It is concise without superfluous details, though the examples could be more compact.

  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 tool's simplicity and the presence of an output schema, the description covers the basic purpose and parameters. However, it lacks detail on the response format (e.g., plain text vs structured data) and error handling, which would complete the context.

  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?

  Schema description coverage is 0%, but the description adds meaning with an Args block: patient_question includes examples, and practice_name states a default. This compensates for the sparse schema, providing clear context beyond type and title.

  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: 'Ask Ravira a patient question and see the AI receptionist's response.' It specifies the verb 'ask' and the resource 'Ravira', and differentiates from sibling tools (e.g., get_ravira_features, search_dental_topics) by focusing on interactive Q&A.

  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 provides examples of suitable questions ('hours, services, pricing, insurance, appointment booking'), implying when to use. However, it does not explicitly state when not to use or compare with alternatives like search_dental_topics for static information.

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

• get_sample_conversationsA
  3.9/5.0
  Behavior2/5

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

  No annotations provided, so description must disclose behavioral traits. Only states it shows examples; lacks details about read-only nature, side effects, pagination, or limitations. Minimal information for a tool with no annotations.

  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 concise sentences that front-load the purpose. Every sentence adds value without redundancy.

  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?

  Output schema exists, so return value details are covered. However, description omits behavioral context like read-only nature or result ordering, leaving minor gaps.

  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?

  No parameters in input schema, so description does not need to add parameter information. Baseline 4 for zero-parameter tools.

  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?

  Clearly states the action ('See real example patient conversations') and resource ('handled by Ravira'). Distinct from siblings like ask_ravira and get_ravira_features, which serve different functions.

  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?

  Implies when to use (to view sample conversations) but does not explicitly specify when not to use or provide alternatives. However, the context is clear enough for an agent to decide.

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

• get_ravira_featuresA
  4/5.0
  Behavior2/5

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

  No annotations are provided, so the description must handle behavioral disclosure. It implies a read-only operation by being a 'get', but does not explicitly state that it has no side effects, requires no authentication, or any other behavioral traits.

  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 concise with two sentences that front-load the primary purpose immediately. Every sentence adds value, with no redundant or vague phrases.

  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 zero parameters and an existing output schema, the description adequately lists key features returned. It could be more precise about the structure of the output, but it provides enough context for an agent to decide when to use this tool.

  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 input schema has zero parameters, and schema description coverage is 100%. The description adds value by specifying what the overview includes (e.g., features, HIPAA compliance), which is beyond the empty schema. Baseline for high coverage is 3, but the additional context warrants a 4.

  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 verb 'Get' and the resource 'full overview of Ravira's features and capabilities'. It lists specific features (AI chat widget, knowledge base, etc.), making the purpose distinct from sibling tools like ask_ravira or search_dental_topics.

  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 explicitly says 'Use this to learn what Ravira offers', providing clear context. It doesn't mention when not to use or alternatives, but the absence of parameters and the overview nature make it self-evident.

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

• request_demoA
  4.6/5.0
  Behavior4/5

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

  The description outlines the outcome: Purnima reaches out to schedule a 20-minute demo. No annotations exist, so the description carries full burden. It could add idempotency or data handling details, but the disclosed behavior is clear and sufficient for a simple demo request.

  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 brief but complete: a two-sentence overview followed by a structured Args list. Every sentence adds value, and the format is easy for an AI 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?

  The description covers purpose, parameters, and outcome. An output schema exists but not shown; the description doesn't need to repeat return values. No critical gaps remain.

  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 coverage is 0%, but the description provides meaningful examples and format guidance for each parameter (e.g., name format, best_time examples). This adds significant value beyond the schema's type definitions.

  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 requests a live demo of Ravira for a dental practice, including the process after submission. It clearly distinguishes from sibling tools like ask_ravira or get_ravira_features.

  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 usage context is implied: use this to request a demo. Siblings cover different functions (Q&A, features, conversations, search), so no ambiguity. However, there is no explicit 'when not to use' or alternative tools mentioned.

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