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mlei06

Elasticsearch MCP (VSee Fork)

by mlei06

get_platform_breakdown

Analyze platform usage by retrieving top platforms or versions with metrics like visit counts and unique users over a specified time period.

Instructions

Get breakdown of top N platforms or platform versions by usage over a time period, can optionally be filtered by account or group. Supports both provider and patient roles. Returns top N items (default 10) plus "Other" category if needed, with metrics per item including visit counts, unique accounts/providers/patients, ratings, and call duration.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
roleYesRole: "provider" for provider platforms/versions, "patient" for patient platforms/versions
breakdownTypeYesBreakdown type: "platform" for platform breakdown (Web/iOS/Android), "version" for platform version breakdown
topNNoNumber of top items to return (default: 10, max: 100). Recommended: do not set over 10.
startDateNoStart date. Format: ISO date (YYYY-MM-DD) or date math (now-30d, now-1y). Default: now-30d.
endDateNoEnd date. Format: ISO date (YYYY-MM-DD) or date math (now). Default: now.
accountNoOptional account name to filter data to
groupNoOptional group name to filter data to
Behavior3/5

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

With no annotations provided, the description carries the full burden and partially discloses behavior by mentioning optional filtering, default values, and return metrics, but lacks details on rate limits, authentication needs, or error handling, which are important for a tool with 7 parameters.

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 appropriately sized and front-loaded, starting with the core purpose and then detailing optional features and return values in a single, efficient sentence with no redundant information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity with 7 parameters and no annotations or output schema, the description is moderately complete but could better address behavioral aspects like data freshness or limitations, though it adequately covers purpose and basic usage.

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 the schema already documents all parameters thoroughly. The description adds marginal value by mentioning optional filtering and default topN behavior, but does not provide significant additional semantics beyond what the schema specifies.

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's purpose with specific verbs ('Get breakdown') and resources ('top N platforms or platform versions by usage'), distinguishing it from siblings like get_usage_summary or get_visit_trends by focusing on platform/version breakdowns rather than general usage or trends.

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

Usage Guidelines3/5

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

The description implies usage context by mentioning filtering options and role support, but does not explicitly state when to use this tool versus alternatives like get_subscription_breakdown or get_rating_distribution, leaving the agent to infer based on the breakdown focus.

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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