DS4AI MCP

generate_head

Creates findability head tags (title, description, canonical, Open Graph, Twitter card) from a flat metadata object for SSR/build-time pages, and returns the HTML lang attribute.

Instructions

Generate the findability head tags (title, description, canonical, Open Graph, Twitter card) for a page from a flat metadata object, as an SSR/build-time string. Also returns the html lang attribute.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "metadata": "<metadata>"
    },
    "name": "generate_head"
  }
}

Input Schema

Name	Required	Description	Default
`metadata`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Aug 21, 2026

TDQS

A4.2/5.0

Behavior4/5

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

With no annotations, the description carries the burden of disclosing behavior. It states that it returns a string and includes the lang attribute, implying a pure, read-only generation operation. It does not mention any side effects, permissions, or error conditions, but for a generator that creates a string, this is acceptable.

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, front-loaded sentence that immediately states the tool's primary function, then adds the lang attribute detail. There is no fluff or redundancy; every part contributes to understanding the tool.

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's simplicity—one parameter, no output schema—the description provides sufficient context about what it returns and the SSR/build-time context. It could have mentioned potential errors or how missing metadata fields are handled, but for a basic generator, it covers the essentials.

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. It briefly mentions 'flat metadata object' and lists the output tags, but does not explain the purpose of each input property (e.g., lang, image, title, siteName, canonical, description) or which are required. The schema lists properties and types, but the description adds minimal value beyond what the schema exposes.

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 identifies the tool's purpose: generating head tags (title, description, canonical, Open Graph, Twitter card) for a page. It specifies the output as an SSR/build-time string and mentions the additional lang attribute, distinguishing it from sibling tools like generate_jsonld, generate_sitemap, and generate_robots, which cover different outputs.

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 (for a page, SSR/build-time) and implies when it might be used. Without explicit alternatives or exclusions, it doesn't fully guide the user away from or toward other tools, but the context is enough for most scenarios.

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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