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key-arg

Statable Analytics

list_prop_keys

Discover custom-property keys recorded for a site, paired with their events, to identify usable event:props: breakdowns in query_stats.

Instructions

List the custom-property keys a site has recorded (with the event each belongs to) — discovery for the event:props: breakdown in query_stats. Returns {"props":[{"key":"plan","event":"Signup","count":N,"first_seen":"RFC3339"}]}.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
siteNoNumeric site_id (preferred, from list_sites) or a domain, e.g. example.com — scheme, www. and path are ignored when matching. If several sites share the domain the call fails and lists their site_ids. Omit for a single-site key.
periodNo"7d"/"30d", or any "Nd" = last N full days (N = 1..90); "month" = current calendar month to date. Default 30d. Or a custom ["YYYY-MM-DD","YYYY-MM-DD"] pair.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.1.0

TDQS

A4.3/5.0
Behavior4/5

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

With no annotations provided, the description carries the full burden and does well by stating what is returned and including a concrete response shape. 'List' also implies a read operation. It does not cover edge cases like empty results or auth requirements, but the core behavior is clear.

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?

A single, dense sentence states the purpose, connects it to a related tool, and includes a sample return payload. Every element earns its place and there is no redundant wording.

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?

The tool is simple with two optional, well-documented parameters. Since no output schema exists, the description compensates by providing a concrete response example. The description, together with the input schema, gives an agent everything needed to call and interpret the result.

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 provides 100% parameter documentation, including site resolution behavior and period formats/defaults. The description adds no parameter-level detail beyond the schema, so the baseline score 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 ('List') with a precise resource ('custom-property keys a site has recorded') and clarifies its role as discovery for the event:props:<key> breakdown in query_stats. This clearly distinguishes it from sibling list tools like list_sites or list_goals.

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?

The description identifies the intended use case: discovering recorded custom-property keys before using the event:props breakdown in query_stats. It gives clear context but does not explicitly state when not to use it or name alternative 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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