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hholen

@lodd/mcp-server

by hholen

get_content_groups

Group pages by URL pattern and compare aggregate metrics for content categories like blog, docs, or app pages.

Instructions

Group pages by URL pattern and get aggregate metrics per group. Useful for comparing how blog vs docs vs app pages perform. Patterns use SQL LIKE syntax where % matches anything.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
siteYesSite domain or UUID
groupsYesGroups to analyze
periodNoTime period30d
filter_osNoOS substring match (e.g. 'iOS')
filter_browserNoBrowser substring match (e.g. 'Chrome')
filter_countryNo2-letter country code (e.g. 'US')
filter_utm_sourceNoExact UTM source (e.g. 'twitter')
filter_device_typeNoDevice type: 'desktop' | 'mobile' | 'tablet'
filter_referrer_containsNoReferrer substring (e.g. 'google')
Behavior3/5

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

No annotations provided. Description implies read-only behavior (get aggregate metrics) and discloses SQL LIKE syntax. However, it does not explicitly state mutability, permissions, rate limits, or other side effects.

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?

Two efficient sentences: first states purpose, second provides use case and pattern syntax. No filler or repetition.

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?

No output schema; description does not specify what aggregate metrics are returned (e.g., pageviews, visitors?). Lacks information on pagination or limits. For a parameter-rich tool with no output schema, this is incomplete.

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 parameters. The description adds context on URL pattern syntax (SQL LIKE) and the grouping concept, which is helpful but not required.

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?

Clearly states the tool groups pages by URL pattern and returns aggregate metrics. Provides concrete examples (blog vs docs vs app) which distinguish it from sibling tools like get_pages or get_analytics.

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?

Gives a use case (comparing page groups) but no explicit guidance on when not to use or alternatives among siblings. The example implies a comparison scenario, but lacks boundaries.

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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