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generate_person_schema

Create structured Person data for search engines by generating JSON-LD schema markup with fields like name, job title, social profiles, and contact information.

Instructions

Generate a Person JSON-LD schema with common fields like name, job title, social profiles, and more.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYesFull name of the person
jobTitleNoJob title or role
urlNoPersonal website or profile URL
imageNoURL to an image of the person
emailNoEmail address
sameAsNoArray of social profile URLs (LinkedIn, Twitter, etc.)
descriptionNoShort bio or description
worksForNoOrganization name
birthDateNoDate of birth (YYYY-MM-DD)
nationalityNoNationality

Implementation Reference

  • The registration and handler implementation of the generate_person_schema tool. It calls the buildPersonSchema helper.
    server.tool(
      "generate_person_schema",
      "Generate a Person JSON-LD schema with common fields like name, job title, social profiles, and more.",
      {
        name: z.string().describe("Full name of the person"),
        jobTitle: z.string().optional().describe("Job title or role"),
        url: z.string().optional().describe("Personal website or profile URL"),
        image: z.string().optional().describe("URL to an image of the person"),
        email: z.string().optional().describe("Email address"),
        sameAs: z
          .array(z.string())
          .optional()
          .describe("Array of social profile URLs (LinkedIn, Twitter, etc.)"),
        description: z.string().optional().describe("Short bio or description"),
        worksFor: z.string().optional().describe("Organization name"),
        birthDate: z.string().optional().describe("Date of birth (YYYY-MM-DD)"),
        nationality: z.string().optional().describe("Nationality"),
      },
      async (params) => {
        const schema = buildPersonSchema(params);
        return {
          content: [
            {
              type: "text" as const,
              text: JSON.stringify(schema, null, 2),
            },
          ],
        };
      }
    );
  • The helper function buildPersonSchema that constructs the Person JSON-LD object.
    function buildPersonSchema(params: {
      name: string;
      jobTitle?: string;
      url?: string;
      image?: string;
      email?: string;
      sameAs?: string[];
      description?: string;
      worksFor?: string;
      birthDate?: string;
      nationality?: string;
    }): object {
      const fields: Record<string, unknown> = { name: params.name };
      if (params.jobTitle) fields.jobTitle = params.jobTitle;
      if (params.url) fields.url = params.url;
      if (params.image) fields.image = params.image;
      if (params.email) fields.email = params.email;
      if (params.sameAs) fields.sameAs = params.sameAs;
      if (params.description) fields.description = params.description;
      if (params.worksFor) {
        fields.worksFor = {
          "@type": "Organization",
          name: params.worksFor,
        };
      }
      if (params.birthDate) fields.birthDate = params.birthDate;
      if (params.nationality) fields.nationality = params.nationality;
      return buildJsonLd("Person", fields);
    }
Behavior2/5

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' a schema but doesn't disclose behavioral traits like whether this creates a new schema object, validates inputs, returns a template, or has any side effects. The description lacks information about permissions needed, rate limits, error conditions, or what the output format looks like beyond 'JSON-LD schema'.

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, efficient sentence that gets straight to the point. It's appropriately sized for a tool with good schema documentation, though it could be slightly more specific about what 'generate' means in practice. No wasted words or unnecessary elaboration.

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 tool with 10 parameters, no annotations, and no output schema, the description is insufficient. It doesn't explain what 'generate' means operationally, what the output looks like, whether all fields are optional except 'name', or how this tool differs from the generic 'generate_schema' sibling. The 100% schema coverage helps, but the description should provide more context about the tool's behavior and purpose.

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 10 parameters thoroughly. The description adds minimal value by listing 'common fields like name, job title, social profiles, and more' which partially maps to the parameters, but doesn't provide additional semantic context beyond what's in the schema descriptions. Baseline 3 is appropriate when schema does the heavy lifting.

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 generates a Person JSON-LD schema with common fields, providing a specific verb ('generate') and resource ('Person JSON-LD schema'). It distinguishes from some siblings like 'generate_article_schema' by specifying the person type, but doesn't explicitly differentiate from the generic 'generate_schema' tool.

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?

No guidance is provided about when to use this tool versus alternatives. The description doesn't mention when to use this specific person schema generator versus the generic 'generate_schema' tool or other schema types like 'generate_organization_schema', nor does it provide any context about prerequisites or appropriate use cases.

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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