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get_stats_digest

Read-only

Retrieve aggregated Remnawave panel statistics for a datetime range, including created and expired users, total traffic, new-user traffic, and new HWID devices.

Instructions

Get Stats Digest Aggregated statistics for a datetime range [start, end): created and expired users, total traffic, traffic spent by users created within the range and new HWID devices. Per-user traffic history is stored with daily granularity (UTC), so the "traffic by new users" metric snaps to whole days at the range edges. [READ] GET /api/system/stats/digest

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
endYesEnd of the range, ISO 8601 datetime with timezone (e.g. 2026-07-16T00:00:00Z). Exclusive.
startYesStart of the range, ISO 8601 datetime with timezone (e.g. 2026-07-15T00:00:00Z). Inclusive.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.1.1

TDQS

A3.5/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the '[READ]' prefix is redundant. The description nonetheless adds real behavioral context absent from the annotations: the half-open interval semantics and the daily UTC granularity caveat explaining that 'traffic by new users' snaps to whole days at the range edges. That caveat materially affects 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?

Content is front-loaded and the metric list is dense and useful. The only waste is the leading 'Get Stats Digest' restatement of the tool name and the redundant '[READ] GET /api/system/stats/digest' line, both of which duplicate structured metadata.

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

Completeness4/5

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

With no output schema, the description compensates by enumerating the returned metrics, and it documents boundary semantics and granularity caveats. An agent has enough to call and interpret it, though it lacks any hint about the response shape or size.

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 coverage is 100% and both parameter descriptions already state inclusive/exclusive boundary behavior, so the description's restatement of [start, end) adds little. Baseline 3 applies when the schema carries parameter semantics.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description names a specific verb and resource (aggregated statistics digest over a datetime range) and enumerates the exact metrics returned: created/expired users, total traffic, traffic by newly created users, and new HWID devices. This clearly distinguishes it from generic siblings like get_stats. It does not, however, explicitly contrast itself with the other stats tools (get_bandwidth_stats, get_stats_user_usage), which would have earned a 5.

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

Usage Guidelines2/5

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

The range-based framing implies when the tool applies, but there is no explicit when-to-use, no exclusions, and no routing to the many sibling stats tools (get_stats, get_bandwidth_stats, get_hwid_devices_stats). An agent must infer selection from the metric list alone.

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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