Skip to main content
Glama

seo_schema

Generate valid JSON-LD structured data for Schema.org Article, FAQPage, or HowTo types. Output is ready to paste into a script tag. Use it with Pipepost to improve SEO on cross-published content.

Instructions

Generate valid JSON-LD structured data for Schema.org Article, FAQPage, or HowTo types. Output is ready to paste into a tag. Costs 1 credit per call. Returns: { jsonld: string, type: 'Article'|'FAQPage'|'HowTo' }. Common errors: invalid type for the supplied content shape (VALIDATION_ERROR), insufficient credits (PAYMENT_REQUIRED).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
typeYesSchema type
dataYesSchema data (varies by type)
Behavior4/5

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

No annotations provided, so description carries full burden. It discloses cost (1 credit), output format, and common errors (VALIDATION_ERROR, PAYMENT_REQUIRED). Could be more explicit about side effects (e.g., read-only nature), but effectively communicates behavioral traits.

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?

Description is concise with three sentences: purpose, output format, and common errors. No redundant information, front-loaded with core 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 two-parameter tool with no output schema, the description covers input, output structure, errors, and cost. Could expand on data parameter constraints per type, but sufficient for agent understanding.

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 coverage is 100% with both parameters described. The description adds error context (invalid type/content) but does not significantly enhance parameter semantics beyond what the schema provides. Baseline 3 is appropriate.

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 generates JSON-LD structured data for specific Schema.org types (Article, FAQPage, HowTo), with output ready for script tags. It distinguishes from siblings like seo_meta and seo_score.

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 mentions cost and output but does not provide explicit guidance on when to use this tool versus alternatives (e.g., seo_meta, seo_score). Usage is implied but no exclusions or comparative context.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/MendleM/pipepost'

If you have feedback or need assistance with the MCP directory API, please join our Discord server