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sandipprajapatiinic

Website Intelligence MCP

analyze_structured_data

Summarize a webpage's JSON-LD structured data blocks. Flag empty or invalid blocks to validate schema markup and catch missing SEO data.

Instructions

Summarize JSON-LD structured data blocks of a webpage and flag empty or invalid blocks

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

B3.3/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It does disclose output behavior (summarizes, flags empty/invalid blocks), which is useful, but it says nothing about whether the tool fetches the URL live, permission requirements, or rate limits.

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?

One sentence, front-loaded with the core action and resource, with zero filler. Both the summarize and flag behaviors are packed into a compact clause.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no annotations and no output schema, the description must carry more weight. It covers the purpose adequately but leaves return-value shape, fetch semantics, and sibling differentiation (analyze_schema) unaddressed.

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% and the single 'url' parameter is not described at all. The name is largely self-explanatory (page to analyze), so the ambiguity is low, but the description adds no format or scoping detail beyond the obvious.

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?

States specific verbs (summarize, flag) and a specific resource (JSON-LD structured data blocks of a webpage). It does not differentiate itself from the sibling analyze_schema, which likely covers the same schema.org/JSON-LD territory, so an agent cannot fully disambiguate from the name alone.

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 when-to-use guidance, no exclusions, and no mention of alternatives such as analyze_schema, which is the obvious overlapping sibling. The agent must infer usage context entirely.

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