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hholen

@lodd/mcp-server

by hholen

get_session_scores

Classify site sessions into engagement buckets: bounced, browsed, engaged, or converted. Define conversion by a specific event for tailored analysis.

Instructions

Classify sessions into engagement buckets: bounced (1 page), browsed (2-3 pages), engaged (4+ pages or event fired), converted (conversion event fired). Optionally specify which event defines 'converted'.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
siteYesSite domain or UUID
periodNoTime period30d
filter_osNoOS substring match (e.g. 'iOS')
filter_browserNoBrowser substring match (e.g. 'Chrome')
filter_countryNo2-letter country code (e.g. 'US')
conversion_eventNoEvent name for 'converted' bucket (e.g. 'signup_complete'). If omitted, any event = converted.
filter_utm_sourceNoExact UTM source (e.g. 'twitter')
filter_device_typeNoDevice type: 'desktop' | 'mobile' | 'tablet'
filter_referrer_containsNoReferrer substring (e.g. 'google')
Behavior4/5

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

Without annotations, description explains classification logic (page counts and event conditions) and optional conversion event. Does not cover potential side effects or authorization, but clearly states behavioral criteria.

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 sentences with no redundancy. First sentence defines core functionality, second adds optional parameter note. Information is efficiently presented and front-loaded.

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?

Provides sufficient context for the tool's purpose and classification rules. Lacks explicit output format description, but given the name and sibling tools, the return type is somewhat implied. No output schema provided.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, but description adds value by defining the engagement buckets that parameters like conversion_event influence. This clarifies the overall context and parameter purpose beyond schema descriptions.

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?

Description explicitly states 'Classify sessions into engagement buckets' with clear definitions for bounced, browsed, engaged, and converted. Distinguishes from sibling tools like get_analytics by specifying session-level classification.

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?

Description implies usage for session engagement analysis but lacks explicit when-to-use or when-not-to-use guidance. No comparisons to siblings like get_session_paths or get_analytics are 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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