Server Quality Checklist

Tool Scores

• generate_dockerfileA
  3.9/5.0
  Behavior4/5

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

  No annotations are provided, so the description carries full burden. It discloses that the tool returns Dockerfile contents as plain text and directs the user to write to file and run docker build. It also references the `docker_image` field from `package_capability`, which adds context. No behavioral surprises or contradictions.

  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 paragraph with a Returns section and an example. It is efficient and front-loaded, but could be slightly more structured (e.g., bullet points for clarity). No wasted sentences.

  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 the simplicity of the tool, the description sufficiently covers the return value and usage pattern. It references the sibling's output field, which adds necessary cross-tool context. The tool has an output schema (implied) and the description explains the return format adequately.

  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%, so baseline is 3. The description adds some context (e.g., takes same inputs as `package_capability` and shows an example) but does not significantly enhance the meaning of individual parameters beyond what the schema already provides.

  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 it generates a Dockerfile for a packaged MCP server, with explicit reference to the sibling tool `package_capability` for context. The verb 'generate' combined with the resource 'Dockerfile' is specific and distinguishable from siblings.

  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?

  Indirectly implies usage after `package_capability` by referencing its inputs, but lacks explicit when-to-use or when-not-to-use guidance. No alternatives are mentioned; however, sibling tools have distinct purposes, so the need for guidance is moderate.

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

• generate_claude_desktop_configA
  4.1/5.0
  Behavior3/5

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

  No annotations are provided, so the description carries full burden. It states the tool generates and returns a JSON snippet, but does not mention any side effects, permissions, or state changes. For a generation tool, this is adequate but could be more explicit about its non-destructive nature.

  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 front-loaded with the main purpose, followed by usage context and an example. It is relatively concise, though the example repeats parameter names already defined. No superfluous sentences.

  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 the tool has 6 parameters and no annotations, the description covers the return value format and usage. The output schema exists, so not detailing its structure is acceptable. It is complete enough for an agent to understand when and how to use it.

  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 coverage is 100%, yet the description adds value: it groups parameters as 'same inputs as package_capability', explains the 'description' parameter's purpose in the generated config, and notes the default for 'registry'. This goes beyond the schema alone.

  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 'generate' and the resource 'claude_desktop_config.json snippet'. It distinguishes from siblings by noting it takes the same inputs as 'package_capability' but returns an 'mcpServers' entry, not a Dockerfile or packaged capability.

  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?

  It explains the tool's output (mcpServers entry) and relation to 'package_capability', implying when to use it (after packaging). It also provides an example. Does not explicitly exclude scenarios, but 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.

• package_capabilityA
  4.5/5.0
  Behavior4/5

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

  No annotations provided, so the description carries full burden. It details return values (a JSON object with four keys) and provides an example. It does not mention side effects or destructive actions, but the tool appears to be a pure builder function without harmful consequences.

  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 (three short paragraphs and an example), front-loaded with the main purpose, and structured with clear sections for returns and example. Every sentence adds value.

  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 that an output schema exists (inferred from context), the description adequately explains the return structure. It covers all necessary aspects: parameter details, return format, and usage ordering relative to siblings.

  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 coverage is 100%, but the description adds significant value beyond schema: it explains the purpose of each parameter in context (e.g., 'the single capability the generated MCP server will expose as a tool' for capability_id) and includes a comprehensive example.

  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 its purpose: 'Build a complete self-hosted MCP server package for an AIMarket capability.' It uses a specific verb ('Build') and resource ('self-hosted MCP server package'), and distinguishes from siblings by noting 'Use this first' and that it assembles everything needed.

  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 first,' providing clear context for when to use it. It does not mention when not to use it or alternatives, but siblings are sufficiently different so no confusion arises.

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