Server Quality Checklist

Tool Scores

• metamodel_list_projectsA
  4.2/5.0
  Behavior4/5

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

  Annotations already indicate readOnlyHint=true and destructiveHint=false. The description adds value by specifying the exact return contents (project names, descriptions, tokens, model names), which is behavioral information not covered by 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: the first clearly states the action, the second lists the return fields. No unnecessary words, front-loaded with purpose.

  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 no parameters and no output schema, the description adequately explains what it does and returns. It could mention that it's a safe read operation, but that is covered by annotations. Overall complete for a simple list 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?

  There are no parameters (0 params), so by the baseline rule, the score is 4. The description does not need to add parameter meaning since none exist.

  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 'Browse' combined with a clear resource 'MetaModel calculators and engineering models', and lists the return fields. This clearly distinguishes it from siblings, which are about getting schema and computing.

  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 implicitly suggests use before other tools to see available projects, but does not explicitly state when to use or when not to. It lacks direct comparison to siblings or exclusions.

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

• metamodel_computeA
  4.4/5.0
  Behavior4/5

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

  Annotations indicate read-only and non-destructive behavior. Description adds useful context: inputs auto-routed by property name, omitted inputs use defaults, and targeting a single model vs all models. No contradictions with 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?

  Four sentences, each earning its place: purpose, input/output behavior, auto-routing, model targeting, and prerequisite. Front-loaded with key action. No fluff.

  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 three parameters, annotations, and no output schema, the description covers the main behavior, parameter guidance, and prerequisite. Could mention that return values are computed outputs, but overall complete enough for effective use.

  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 covers all parameters (100%). Description adds meaning: explains auto-routing for 'inputs' and recommends omitting 'model' for all outputs. This adds value beyond the schema's literal 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?

  Clearly states the tool runs a computation on a MetaModel project with input sending and output retrieving. It distinguishes from sibling tools (metamodel_list_projects, metamodel_get_schema) by describing the core computation action and auto-routing behavior.

  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?

  Explicitly tells the agent to use metamodel_get_schema first to discover inputs/outputs, and provides guidance on the 'model' parameter (omit for all models, recommended). Lacks explicit when-not-to-use or alternative exclusions, but clear context is present.

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

• metamodel_get_schemaA
  4.5/5.0
  Behavior4/5

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

  Annotations already declare readOnlyHint=true and destructiveHint=false, and the description confirms a read-only operation ('Get'). It adds useful detail about the returned content (model names, input parameters, output fields), enhancing transparency without contradiction.

  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 short sentences: the first states the core function, the second provides a critical prerequisite. No excess words, front-loaded with essential information.

  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?

  For a simple tool with one parameter and no output schema, the description adequately covers purpose, prerequisite, and return content. It is complete given the tool's complexity and available structured 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?

  The sole parameter 'token' is well-described in the schema, and the description adds context by referencing metamodel_list_projects as the source. With 100% schema coverage, the description adds marginal but helpful value 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 clearly states the tool's purpose: to get the input/output schema for a published MetaModel project. It specifies the resource (schema) and the verb (get), and distinguishes from siblings like metamodel_list_projects and metamodel_compute by focusing on schema retrieval.

  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 a token from metamodel_list_projects,' providing a clear prerequisite and hinting at the workflow order. While it doesn't specify when not to use or list alternatives, this guidance is sufficient for correct invocation.

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