Server Quality Checklist

Tool Scores

• list_templatesC
  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 states the tool lists templates and returns a formatted list, but it doesn't cover important aspects like whether this is a read-only operation, potential side effects, error handling, or performance considerations. For a tool with zero annotation coverage, this leaves significant gaps in understanding its 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 concise and well-structured, with a clear purpose statement followed by brief sections for arguments and returns. It avoids unnecessary words and is front-loaded with the main functionality. However, it could be slightly more efficient by integrating the optional note into the purpose statement.

  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 lack of annotations and output schema, the description is incomplete. It covers the basic purpose and parameter but misses behavioral details, usage context, and output specifics. For a tool with no structured support, the description should provide more comprehensive guidance to be fully helpful to an 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 description adds some value beyond the input schema by explaining that the 'language' parameter is optional and used for filtering. However, with 0% schema description coverage and only one parameter, the description doesn't fully compensate—it lacks details on format, constraints, or examples. Since there's only one parameter, the baseline is higher, but the information provided is minimal.

  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: 'list available templates for MCP server creation.' This specifies the verb ('list'), resource ('templates'), and context ('for MCP server creation'), making it easy to understand what the tool does. However, it doesn't explicitly distinguish this tool from its siblings (e.g., create_mcp_server, get_ai_guidance, save_workflow), which would be needed for a score of 5.

  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 minimal usage guidance. It mentions an optional 'language' filter but doesn't explain when to use this tool versus alternatives like create_mcp_server or other siblings. There's no context on prerequisites, typical scenarios, or exclusions, leaving the agent with little direction on appropriate usage.

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

• save_workflowC
  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 states 'save' implies a write operation but doesn't cover permissions, idempotency, error handling, or what 'confirmation message' entails. This is inadequate for a mutation tool with zero annotation coverage.

  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 with the core purpose in the first sentence. The Args and Returns sections are structured but could be more integrated; overall, it's efficient with minimal waste.

  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 mutation tool with 3 parameters, 0% schema coverage, no annotations, and no output schema, the description is incomplete. It lacks details on behavioral traits, parameter constraints, error cases, and the nature of the return value, making it insufficient for reliable agent 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?

  Schema description coverage is 0%, so the schema provides no parameter descriptions. The description lists parameters (name, description, steps) and adds that steps are a 'list of workflow steps', offering some semantic value beyond the bare schema. However, it doesn't detail format, constraints, or examples, leaving significant gaps.

  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 verb 'save' and resource 'creation workflow' with the purpose 'for reuse', making the tool's function understandable. However, it doesn't differentiate from sibling tools like 'list_templates' or 'create_mcp_server', which might be related to workflow management, so it doesn't achieve full sibling differentiation.

  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 alternatives like 'list_templates' or 'create_mcp_server'. It mentions 'for reuse' but doesn't specify prerequisites, timing, or exclusions, leaving the agent with minimal context for tool selection.

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

• create_mcp_serverB
  3.4/5.0
  Behavior4/5

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

  With no annotations provided, the description carries full burden for behavioral disclosure. It does well by including an 'IMPORTANT NOTES' section that covers platform limitations (AI sampling not supported), coding standards, and implementation details (process cleanup, error handling, SDK patterns). However, it doesn't mention potential side effects like file system changes or whether this is a one-time creation vs. incremental update.

  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 clear sections (purpose, important notes, args, returns) and front-loads the core functionality. However, some sentences in the 'IMPORTANT NOTES' section could be more concise, and the parameter explanations vary in detail level, making it slightly uneven.

  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?

  For a 6-parameter creation tool with no annotations and no output schema, the description provides adequate coverage of what the tool does and its parameters. The 'Returns' section helps compensate for the missing output schema. However, it lacks information about error conditions, validation rules, or what happens when creation fails, which would be important for a tool that modifies the environment.

  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 0%, so the description must compensate. The 'Args' section provides meaningful explanations for all 6 parameters, adding value beyond the bare schema. However, some explanations are minimal (e.g., 'Description of what the server does') and don't clarify constraints like what makes a 'valid Python identifier' or the implications of different 'language' choices.

  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: 'Create a new MCP server based on specifications.' It specifies the verb ('create') and resource ('MCP server'), making the action clear. However, it doesn't explicitly differentiate from sibling tools like 'list_templates' or 'save_workflow', which would be needed for 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 alternatives. While it mentions 'template_type' and 'features' parameters, it doesn't explain when to choose 'basic' vs 'fastmcp_server' templates or what 'tools, resources, prompts' features entail. There's no mention of prerequisites or comparison with sibling tools like 'list_templates'.

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

• get_ai_guidanceA
  3.5/5.0
  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 adds useful context: the tool is deterministic (not AI-generated), provides structured guidance with code patterns, and includes important notes on limitations (e.g., AI sampling not supported). However, it lacks details on permissions, rate limits, or error handling, which are important for a guidance tool.

  Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

  Conciseness3/5

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

  The description is appropriately sized but not optimally structured. It front-loads the purpose but includes a lengthy 'IMPORTANT NOTES' section that, while relevant, could be more integrated. The sentences earn their place, but the flow could be improved for better readability and focus on the tool's core function.

  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 complexity (2 parameters, no output schema, no annotations), the description is moderately complete. It covers purpose, usage, and parameter semantics adequately but lacks details on output format (beyond 'structured guidance'), error cases, or examples. For a guidance tool with no output schema, more information on return values 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?

  The schema description coverage is 0%, so the description must compensate. It adds meaning by explaining 'topic' as 'Topic to get guidance on (best_practices, security, performance, typing, etc.)' and 'server_type' as 'Type of server for contextualized advice,' which clarifies their purposes beyond the schema's basic titles. However, it doesn't provide examples or constraints for these parameters.

  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: 'Get structured guidance for MCP server development' and specifies it provides 'structured, deterministic guidance instead of AI-generated content.' This distinguishes it from AI-generated assistance but doesn't explicitly differentiate it from sibling tools like 'create_mcp_server' or 'list_templates' in terms of guidance vs. creation/listing 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?

  The description provides clear context on when to use this tool: for 'structured, deterministic guidance' on MCP server development topics. It explicitly states 'For dynamic AI assistance, use Claude Desktop's built-in capabilities directly,' offering an alternative. However, it doesn't specify when NOT to use it relative to sibling tools like 'create_mcp_server' or 'save_workflow.'

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