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hholen

@lodd/mcp-server

by hholen

get_source_conversions

Compare traffic sources by conversion rate to identify which referrers, UTM campaigns, and links drive the most conversions, along with average time to convert per source.

Instructions

Compare traffic sources by conversion rate for a specific event. Shows which referrers, UTM campaigns, and trackable links drive the most conversions, plus average time to convert per source.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
siteYesSite domain or UUID
limitNoMax results (1-1000)
periodNoTime period30d
event_nameYesThe conversion event name (e.g. 'signup_click', 'purchase')
Behavior3/5

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

With no annotations provided, the description carries full burden. It discloses the tool's computational result (comparison of conversion rates and average time) but does not state that it is a read-only query, mention authentication needs, rate limits, or whether data is aggregated. It is functional but minimally transparent.

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, front-loaded with the primary purpose, followed by specific outputs. Every clause adds value; no filler or redundancy.

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 tool with 4 parameters, no output schema, and no annotations, the description covers the core functionality and expected results. However, it could mention returned data structure, sorting (e.g., by conversion rate), or how limit affects results, though not essential.

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 clear parameter descriptions (e.g., 'event_name' explanation includes examples). The tool description adds no additional parameter-level meaning beyond what the schema provides, so baseline score of 3 applies.

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 compares traffic sources by conversion rate for a specific event, listing specific metrics (referrers, UTM campaigns, trackable links, average time to convert). This distinguishes it from siblings like get_traffic_sources, which likely lacks the conversion focus.

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 analyzing source conversion performance but provides no explicit guidance on when to use this tool versus alternatives like get_event_counts or get_conversion_pages. No exclusions or context are given.

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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