Get Live Visitors
get_liveReal-time snapshot: active visitors right now plus the most recent events. Ignores range.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| site | Yes | Site handle from list_sites. |
get_liveReal-time snapshot: active visitors right now plus the most recent events. Ignores range.
| Name | Required | Description | Default |
|---|---|---|---|
| site | Yes | Site handle from list_sites. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, so safety is covered. The description adds useful behavioral context: it returns active visitors and recent events, and it ignores the range parameter, making the tool's real-time nature explicit. This goes beyond the annotation without contradicting it.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two concise sentences, front-loaded with the core concept ('Real-time snapshot') and free of fluff. Every word contributes meaning, making it highly efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple one-parameter, read-only tool with no output schema, the description covers the essential behavior: what it returns, its real-time nature, and its range-ignoring behavior. It doesn't detail response formatting, but that isn't critical for this type of tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% for the single 'site' parameter, which is clearly described as 'Site handle from list_sites.' The description doesn't add further parameter detail, but the baseline 3 applies because the schema already fully documents the parameter.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states a specific verb+resource: real-time snapshot of active visitors and recent events. It distinguishes itself from sibling tools by explicitly noting 'Ignores range,' which separates it from range-based analytics like get_overview and get_traffic_sources.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use this tool: when you need a real-time snapshot without date filtering. It doesn't explicitly name alternatives or exclusions, but 'Ignores range' provides clear context that this is the live-data tool among range-parameter siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool addresses a distinct analytics facet (overview, traffic, geo, audience, pages, funnel, live, weekly report, site context, site list) with no overlapping purposes. An agent can easily choose the right tool based on the question.
All tools follow a consistent verb_noun pattern (get_*) except list_sites, which still uses a clear verb_noun structure. The naming is uniform and predictable.
With 10 tools, the set is well-scoped for an analytics server, covering both summary and breakdown views without unnecessary bloat. Each tool earns its place.
The tool set covers core analytics needs: overview, traffic sources, audience, geo, pages, funnel, live, and weekly comparisons. Minor gaps like custom date ranges or event detail drill-downs are not critical for standard store analytics.