Server Quality Checklist

Tool Scores

• rewrite_tool_descriptionA
  4/5.0
  Behavior3/5

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

  No annotations are provided, so the description carries the transparency burden. It discloses the output ('Returns the improved description ready to paste into your MCP server') but doesn't disclose any limitations or side effects, though it's likely a pure text transformation.

  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 two sentences, front-loads the main purpose, and includes no unnecessary information.

  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?

  The tool has a simple purpose, 4 parameters with full schema coverage, and the description explains the return value. It could benefit from explicit usage guidance relative to sibling tools, but it is otherwise adequate.

  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 each parameter has a description. The tool description mentions best practices that incorporate parameter hints, but doesn't add specific parameter semantics beyond the 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 'Rewrite a weak tool description into a high-quality, LLM-optimized version', which clearly identifies the action and resource. It also distinguishes itself from sibling tools by focusing on rewriting rather than auditing or fetching best practices.

  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 implies use when a tool description is weak and needs improvement, by saying 'Rewrite a weak tool description'. It doesn't explicitly mention alternative tools or exclusions, but the context is clear enough.

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

• audit_toolA
  4.2/5.0
  Behavior4/5

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

  With no annotations, the description carries the full burden. It explicitly discloses the return value (0-100 quality score, list of detected smells, concrete fix suggestions), giving a transparent picture of behavior. It does not mention side effects or permissions, but as a read-only audit tool, the output description is sufficient for most contexts.

  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 exactly two sentences: the first states the purpose, the second states the output and usage context. It is front-loaded, concise, and every sentence adds value with no superfluous content.

  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 tool with 3 parameters and no output schema, the description explains the output format (score, smells, fixes) and the context (before publishing). It lacks explicit error handling or limitations, but given the simplicity of an audit tool, this is adequate. A slightly higher score would require explicitly stating it is read-only or defining 'LLM reliability.'

  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%, meaning all parameters are already documented in the schema. The description does not add parameter-specific details beyond the overall purpose, which implies the 'description' is the main artifact being audited. 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.

  Purpose5/5

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

  The description clearly states the tool audits a single MCP tool description for LLM reliability, using the specific verb 'Audit' and specifying the resource ('single MCP tool description'). This distinguishes it from sibling tools like audit_tool_list (likely batch auditing) and rewrite_tool_description (rewriting descriptions).

  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 a clear usage scenario: 'Use this before publishing any MCP server.' It implies the tool is for pre-publication validation. While it does not explicitly name alternatives or list when-not-to-use conditions, the qualifier 'single' differentiates it from batch tools like audit_tool_list, offering adequate guidance.

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

• audit_tool_listA
  4.2/5.0
  Behavior4/5

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

  With no annotations provided, the description carries the full behavioral burden. It goes beyond a simple statement of action by explaining the logic behind the tool: detecting overcrowding with a specific research-based accuracy threshold and ranking/flags. This provides meaningful context about what the tool does and why, though it does not delve into edge cases or exact output formatting.

  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 two sentences, front-loaded with the core purpose, and each sentence adds value. The second sentence provides supporting evidence for the 'overcrowding' check, making the description both informative and concise without waste.

  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 tool with a single parameter and no annotations, the description is reasonably complete: it explains what the tool does, why (research-based threshold), and what outputs to expect (ranking, flags). However, without an output schema, it could be more explicit about the exact structure of the returned data, but the description's mention of ranking and flags covers the essentials.

  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 already describes the only parameter ('tools') as 'Array of tool objects to audit,' which provides 100% coverage. The tool description does not add additional parameter-level meaning beyond what the schema provides, so the baseline score of 3 is appropriate.

  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 a specific verb and resource: 'Audit an entire list of tools at once.' It distinguishes itself from sibling 'audit_tool' by emphasizing the batch aspect, and enumerates key capabilities (detect overcrowding, rank by quality score, flag worst offenders).

  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 makes it clear this tool is for auditing a list of tools (batch processing), which gives a clear usage context. However, it does not explicitly mention alternatives or exclusion criteria, such as 'for a single tool, use audit_tool instead.' The context is clear but lacks explicit differentiation from sibling tools.

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

• get_best_practicesA
  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 burden. It clearly implies a read-only operation ('Return the current checklist') and adds context about the source (research + testing). However, it does not disclose details like response format, potential size, or any limitations, which would enhance transparency 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?

  The description is two sentences, front-loaded with the core purpose, and includes only essential information. Every phrase earns its place, making it highly concise and well-structured.

  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?

  The tool is simple (0 params, no output schema), and the description explains what it returns and when to use it. It could add the return format, but the term 'checklist' sufficiently implies a list, making the description complete enough for its low complexity.

  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 is empty (0 parameters), and the schema description coverage is 100%, so the baseline is 4. The description appropriately avoids mentioning parameters since there are none, and it adds no unnecessary parameter-related details.

  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 uses a specific verb ('Return') and clearly identifies the resource ('checklist of MCP tool-description best practices'). It also distinguishes itself from sibling tools like audit_tool and rewrite_tool_description by focusing on a reference checklist rather than action-oriented operations.

  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 clearly states when to use the tool: 'Use this as a reference when writing new tools.' It provides a clear context but does not mention exclusions or alternatives, though the sibling tools are distinct in purpose.

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