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SEODesignLab

@seodesignlab/mcp-server

by SEODesignLab

get_content_brief

Create a structured content brief for any target keyword, including recommended word count, headings, LSI terms, title/meta suggestions, and content structure guidelines.

Instructions

Generate a POP (PageOptimizer Pro) content brief for a target keyword.

Price: $2.00 (x402 on Base)

Returns a detailed content brief including:

  • Target keyword analysis

  • Recommended word count and headings

  • LSI terms and semantic keywords

  • Title and meta description suggestions

  • Content structure guidelines

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
keywordYesTarget keyword for the content brief
languageNoLanguage code (default: 'en')
locationNoOptional location/geo targeting (e.g. 'United States', 'Florida')
Install Server

TDQS

A3.7/5.0
Behavior3/5

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

With no annotations, the description carries the full burden for behavioral disclosure. It does disclose the price, the fact that it returns a detailed brief, and provides a bulleted list of output contents. However, it does not mention whether this is a paid/external API call with side effects, potential rate limits, or any authorization requirements. The output detail is helpful but incomplete for a paid tool.

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 compact and front-loaded: it states the action and output type immediately, then gives a clear bulleted list of what the brief includes. The price line is useful context, though slightly detracts from the core flow. Overall every sentence earns its place despite minor formatting overhead.

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 moderate complexity and no output schema, the description compensates well by enumerating the key sections of the returned brief. It omits error/edge-case behavior and does not mention language/location effects, but the essential information for calling the tool correctly (target keyword, output expectation, price) is present.

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 fully documents all three parameters. The description adds no meaning beyond what the schema provides, aside from reinforcing that 'keyword' is the target. Baseline 3 is appropriate when the schema carries the parameter documentation burden.

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 uses a specific verb ('Generate') and names a distinct resource ('POP content brief'), with the target keyword as the object. This clearly distinguishes it from siblings like backlink_profile or on_page_audit, none of which produce content briefs. It is unambiguous what this tool does.

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 implies usage for content brief creation but does not explicitly state when to prefer this over keyword_research or serp_analysis, nor does it mention any exclusions. The context is clear enough that an agent can infer the primary use case, but no direct comparative guidance is provided.

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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