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Howseen

by ai.howseen
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Get AI referral traffic

get_ai_referrals
Read-only

Real visits AI assistants send to the brand: GA4 sessions and revenue per assistant (ChatGPT, Perplexity, Gemini, Claude, Copilot...) and the pages they land on, an estimate of hidden AI visits (shown apart, never added), and the AI assistants that read the brand's Howseen-hosted blog pages (last 30 days). Use it to prove that AI visibility turns into traffic.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "get_ai_referrals"
  }
}

Input Schema

NameRequiredDescriptionDefault
daysNoPeriod in days: 7, 28 (default) or 90.
brandNoBrand id, name or domain (from list_brands). Optional when the account has a single brand.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already cover the read-only, non-destructive, open-world profile, so the description isn't obligated to restate safety. It does add a genuinely behavioral detail beyond annotations: the hidden AI visit estimate is "shown apart, never added," which prevents an agent from misreading totals as including estimates.

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?

Content is front-loaded and the two sentences carry no filler. The first sentence is dense and run-on, packing three distinct data groups into one clause chain, which slightly hurts scannability.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema, the description must convey what comes back, and it does: assistant-level sessions and revenue, landing pages, a separately reported estimate, and blog-page readers. Combined with fully documented parameters and read-only annotations, an agent has everything needed to call it correctly.

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%, so both `days` (7/28/90, default 28) and `brand` (id, name, or domain, optional for single-brand accounts) are fully documented in the schema. The description adds no parameter-level detail, and its "last 30 days" note refers to the blog-reader section rather than the days parameter, so baseline 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?

States a specific verb and resource (AI referral traffic) and then enumerates exactly what is inside: GA4 sessions and revenue per assistant, landing pages, hidden-visit estimate, and AI readers of the Howseen blog. That content breakdown clearly separates it from siblings like get_analytics or get_top_sources, which cover general traffic rather than assistant-attributed referrals.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

"Use it to prove that AI visibility turns into traffic" gives a concrete use case that tells the agent when this is the right choice. It stops short of naming an alternative or stating when-not to use it (e.g., versus get_analytics), so it falls short of a 5.

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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