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validate_element

Validate elements like personas, skills, and agents for correctness and best practices in the DollhouseMCP server to ensure proper functionality and compatibility.

Instructions

Validate an element for correctness and best practices

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYesThe element name to validate
typeYesThe element type
strictNoWhether to apply strict validation rules

Implementation Reference

  • Tool registration for 'validate_element' including schema and handler that delegates to server.validateElement
    tool: {
      name: "validate_element",
      description: "Validate an element for correctness and best practices",
      inputSchema: {
        type: "object",
        properties: {
          name: {
            type: "string",
            description: "The element name to validate",
          },
          type: {
            type: "string",
            description: "The element type",
            enum: Object.values(ElementType),
          },
          strict: {
            type: "boolean",
            description: "Whether to apply strict validation rules",
            default: false,
          },
        },
        required: ["name", "type"],
      },
    },
    handler: (args: ValidateElementArgs) => server.validateElement(args)
  • Type definition for input arguments to validate_element tool
    interface ValidateElementArgs {
      name: string;
      type: string;
      strict?: boolean;
    }
  • IToolHandler interface definition for validateElement method signature
    validateElement(args: {name: string; type: string; strict?: boolean}): Promise<any>;
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 mentions validation for 'correctness and best practices' but doesn't specify what happens during validation—e.g., whether it returns detailed errors, requires specific permissions, has rate limits, or affects system state. This is a significant gap for a tool with no 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.

Conciseness5/5

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

The description is a single, efficient sentence that directly states the tool's purpose without unnecessary details. It is front-loaded and wastes no words, making it easy for an agent to parse quickly.

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 complexity of validation (which could involve error reporting or system checks), no annotations, and no output schema, the description is incomplete. It doesn't explain what the tool returns (e.g., validation results or status) or behavioral aspects, leaving gaps that could hinder correct agent invocation.

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 the schema already documents all parameters (name, type, strict). The description adds no additional meaning beyond what's in the schema, such as explaining validation rules or how 'strict' affects outcomes. Baseline 3 is appropriate when the schema handles parameter documentation effectively.

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 as 'Validate an element for correctness and best practices,' which includes a specific verb ('validate') and resource ('element'). However, it doesn't distinguish this from potential sibling tools like 'check_github_auth' or 'get_element_details,' which might also involve validation-like operations, so it lacks explicit 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. For example, it doesn't specify if this should be used before 'create_element' or after 'edit_element,' nor does it mention any prerequisites or exclusions, leaving the agent to infer usage from context alone.

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

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