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Measure.events Analytics

by io.github.meetclawdius
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AI agents

get_agents
Read-only

Every AI agent that fetched the site: operator, purpose (assistant, training, search), requests, top page.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "site_key": "<site_key>"
    },
    "name": "get_agents"
  }
}

Input Schema

NameRequiredDescriptionDefault
toNoEnd date, YYYY-MM-DD (UTC, inclusive).
fromNoStart date, YYYY-MM-DD (UTC, inclusive).
periodNoTime period. Ignored when from and to are given.
site_keyYesThe site's tracking ID (site_key), from list_sites.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

B3.4/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true and openWorldHint=false, so the safety profile is covered. The description adds useful return-field context by naming operator, purpose, requests, and top page, but it does not describe pagination, ordering, defaults, or result format.

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 front-loaded sentence with no filler. It efficiently lists the key returned attributes and earns every word.

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 read-only analytics tool with full schema coverage and clear annotations, the description is nearly complete. It lists the returned fields, though it omits return format and pagination details that could matter since no output schema exists.

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 all four parameters are already documented in the input schema. The description adds no parameter-level meaning beyond what the schema provides, which is acceptable but not additive.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly identifies the resource and returned fields: every AI agent that fetched the site, with operator, purpose, requests, and top page. It does not explicitly distinguish this from the sibling get_agent_report, so it stops short of a 5.

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

Usage Guidelines2/5

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

The description provides no explicit guidance on when to use this tool versus alternatives such as get_agent_report or get_site_analytics. It also does not mention date-range or period selection behavior, leaving usage entirely implied.

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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