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events.property_values

Read-only

Retrieves the most common string values for a property on a given event, ranked by occurrence count. Helps identify value space for cohort or segment filtering.

Instructions

Top distinct values a string-typed property has taken on a specific event in the period, ranked by occurrence count. Useful when you need to know the value space before filtering — e.g. cohort definitions, segment filters, "what values does plan take on signup?".

Response shape:

{
  event: "signup",
  property: "plan",
  period: "30d",
  values: [
    { value: "free", count: 412 },
    { value: "pro",  count: 138 },
    { value: "growth", count: 22 }
  ]
}

Examples:

  • "what plans do signups come from" → event="signup", property="plan"

  • "which countries hit the checkout event" → event="checkout", property="country" (only if you instrument it as a property; otherwise use traffic.breakdown)

  • "what source values does the lead event carry" → event="lead", property="source"

Limitations: STRING properties only — same scope as cohort filter values (cohort filtering is string-equality only). Numeric / boolean / money properties are out of scope. Results are capped at limit (default 50, max 200) so very high-cardinality properties (user_id, session_id, URLs) are truncated to the top-N by count. Events without the property at all are skipped — only rows where the property is present and non-empty contribute.

Pairs with: events.observed_schema to discover which properties an event actually fires; cohorts.create to scope a cohort by a specific value of those.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
eventYesEvent name (e.g. "signup", "checkout_completed"). Required — values are scoped to one event at a time.
limitNoMax distinct values to return, ranked by count desc (1-200). Defaults to 50.
periodNoTime period. Use "today", "yesterday", "7d", "30d", "90d", or a custom range as "YYYY-MM-DD:YYYY-MM-DD" (e.g. "2026-01-01:2026-03-31"). Defaults to "30d".
propertyYesProperty key on the event (e.g. "plan", "source"). Required. Only string-typed properties are surfaced; pass a numeric/boolean property name and you'll get an empty `values` array.
project_idNoTarget project ID (e.g. "proj_abc123"). Required when the credential has access to multiple projects. If omitted and only one project is accessible, that project is used automatically. Call `projects.list` to discover available project IDs.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
eventYes
periodYes
valuesYes
propertyYes
Behavior5/5

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

Annotations declare readOnlyHint, and description adds behavior: only string properties, non-string returns empty array, results capped at limit, events without property skipped. No contradiction.

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?

Front-loaded with purpose, followed by examples and limitations. Every sentence earns its place. Concise yet comprehensive, no unnecessary text.

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?

For a 5-parameter tool with output schema, the description covers return shape (via example), use cases, limitations, and pairing with siblings. All critical context for correct invocation is provided.

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

Parameters5/5

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

Schema coverage is 100%; description adds value with examples (event='signup', property='plan'), period format details, limit defaults, and behavior for invalid property type. Each parameter's role and constraints are well explained.

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 returns top distinct values for a string-typed property on an event, ranked by count. It differentiates from siblings by referencing events.observed_schema for property discovery and traffic.breakdown for country data, and pairs with cohorts.create.

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

Usage Guidelines5/5

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

Explicitly states when to use: to understand value space before filtering (cohort definitions, segment filters). Provides examples and limitations (string only, capped results, omitted events). Also suggests alternative pattern with other tools.

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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