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Get analytics

get_analytics
Read-onlyIdempotent

Views, unique visitors, completion rate, average time and leads for the last days (default 30, today included, UTC), with daily counts and the change against the previous period. For one demo (demoId): the step funnel (sessions that reached each published step) with where viewers drop off and the biggest drop, screen visits and hotspot clicks (clickable), recent sessions and traffic sources. Linear demos: the drop is from the previous step. Branched demos (branched: true, choices or step jumps): steps on different paths can’t be compared in list order, so the drop is left, the sessions that stopped at that step without finishing, with each step’s path, plus paths and a breakdown per choice. Without demoId: the workspace totals and top demos. Free plans get view counts only (detailed: false).

Requires: demos:read, analytics:read.

Input Schema

NameRequiredDescriptionDefault
daysNo
demoIdNoOne demo (default: the whole workspace).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.7/5.0
Behavior5/5

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

Annotations already declare read-only, idempotent, non-destructive behavior, but the description adds substantial context beyond them: required scopes, UTC/today-inclusive time semantics, free-plan view-only behavior, and different drop-off semantics for linear vs branched demos. These details materially affect interpretation of results.

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?

The description is dense but front-loads the primary metrics and then explains demo-level and branched behavior. It is appropriately sized for the complexity, though long sentences make it slightly harder to scan than a bulleted structure would be.

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 and a complex, context-dependent response, the description explains what is returned in each mode, including funnel steps, drop-off behavior, traffic sources, paths, and plan limitations. Required permissions are also stated, leaving little an agent needs before calling it.

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 description coverage is only 50%, but the description compensates well: it explains that days defaults to 30, includes today, uses UTC, and that demoId switches the entire response shape from workspace totals to per-demo funnel, path, and session analytics. This adds meaning well beyond the schema.

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 names the exact metrics returned (views, unique visitors, completion rate, average time, leads) and clearly distinguishes workspace-level totals from single-demo analytics. No sibling tool covers analytics, and the scope is unambiguous.

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?

It clearly states the two usage modes: omit demoId for workspace totals, provide demoId for per-demo funnel and session analytics. It also explains the free-plan limitation, though it does not name alternatives or explicit when-not-to-use conditions, which are less relevant here because no sibling analytics tool exists.

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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