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Marc-Lou-Org

@datafast/mcp-server

by Marc-Lou-Org

Get Visitors by Device

get_devices

Retrieve visitor counts and revenue segmented by device type (desktop, mobile, tablet) with optional filters for date, location, source, and more.

Instructions

Get visitor counts and revenue broken down by device type (desktop, mobile, tablet).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
osNoFilter by operating system
refNoFilter by ref parameter
viaNoFilter by via parameter
cityNoFilter by city
pageNoFilter by page path
endAtNoEnd date in ISO 8601 format (e.g. 2025-01-31T23:59:59Z)
limitNoNumber of results to return (1-1000, default: 100)
deviceNoFilter by device type (desktop, mobile, tablet)
offsetNoNumber of results to skip (default: 0)
regionNoFilter by region
sourceNoFilter by source parameter
browserNoFilter by browser (e.g. Chrome, Safari)
countryNoFilter by country code (e.g. US, GB)
startAtNoStart date in ISO 8601 format (e.g. 2025-01-01T00:00:00Z)
hostnameNoFilter by hostname
referrerNoFilter by referrer URL
timezoneNoIANA timezone (e.g. America/New_York). Defaults to website timezone
utm_termNoFilter by UTM term
entry_pageNoFilter by entry page path
utm_mediumNoFilter by UTM medium
utm_sourceNoFilter by UTM source
utm_contentNoFilter by UTM content
utm_campaignNoFilter by UTM campaign
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It only states that it retrieves counts and revenue by device, but it does not disclose behavior such as aggregation scope, pagination, authentication requirements, or the structure of the returned data. The tool has 23 filter parameters, yet the description gives no insight into how they affect the request or response, leaving significant gaps.

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?

The description is a single, efficient sentence that front-loads the key information: what is returned (visitor counts and revenue) and the grouping dimension (device type). There is zero redundancy or irrelevant detail, making it highly concise and well-structured.

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?

Given the tool's complexity (23 parameters, no output schema, no annotations), the description is far too minimal. It fails to explain the return structure, pagination behavior, available filters, or any usage nuances. A more complete description would mention at least that it returns grouped analytics and can be filtered by date and other dimensions, but it does not.

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?

The input schema has 100% coverage, so all 23 parameters are individually described. The description adds no extra meaning beyond the schema—it merely restates the purpose of the 'device' parameter. Since the schema already handles parameter details, the baseline of 3 is appropriate.

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 'Get' and clearly states the resource: 'visitor counts and revenue' broken down by device type. This explicitly distinguishes it from sibling analytics tools like get_browsers and get_operating_systems, making its purpose unambiguous.

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 through the phrase 'by device type', but it does not explicitly state when to use this tool versus alternatives, nor does it mention exclusions or provide context on when this breakdown is appropriate. Since the title and description imply device-specific analytics, it earns a 3 for implied usage rather than a 2 for no guidance.

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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