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queryAnalytics

Retrieve NextDNS analytics metrics such as resolution status, device usage, protocols, and destinations. Supports time-series data and filtering by device or status.

Instructions

Query NextDNS analytics metrics.

Metrics: - status: Query resolution status (default, blocked, allowed, relayed). - devices: Queries per device. - protocols: DNS transport protocol (DoH, DoT, Do53 UDP/TCP, DoQ). - queryTypes: DNS record types requested (A, AAAA, CNAME, etc.). - ipVersions: IPv4 vs IPv6 queries. - dnssec: DNSSEC validation results. - encryption: Encrypted vs unencrypted queries. - reasons: Why queries were blocked or allowed. - ips: Top source IPs. - destinations: Top destinations; requires destination_type such as countries or gafam.

Set series=true to fetch time-series data instead of aggregate totals. Time values can be Unix timestamps or relative strings like -1d. Note: series=true is not supported when metric="domains".

Optional filters: - cursor: Pagination cursor from a previous response. - device: Filter analytics to a single device id. - status: For the domains metric, filter by resolution status. - root: For the domains metric, group results by root domain (boolean).

Examples: - totals: queryAnalytics(metric="status", profile_id="abc123", from_time="-1d") - time series: queryAnalytics(metric="status", profile_id="abc123", from_time="-1d", series=true) - destinations: queryAnalytics(metric="destinations", profile_id="abc123", from_time="-1d", destination_type="countries")

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
rootNo
limitNo
cursorNo
deviceNo
metricYes
seriesNo
statusNo
to_timeNo
intervalNo
partialsNo
timezoneNo
alignmentNo
from_timeNo
profile_idYes
destination_typeNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

With no annotations, the description discloses important behavioral traits like time format flexibility and the series restriction, but could mention read-only nature and lack of destructive side effects.

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?

Well-structured with bullet points and examples, front-loaded with purpose. Slightly lengthy but each part adds value.

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?

Given the complexity (15 params, output schema exists), the description provides sufficient context for typical use cases, though some parameters are left unexplained.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, but the description covers many key parameters (metrics, series, time, filters) adding meaning beyond schema. Some parameters like limit, interval remain undocumented.

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 'Query NextDNS analytics metrics' and lists numerous specific metrics, making the tool's purpose explicit and distinct from siblings like plotAnalytics, dohLookup, etc.

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?

Provides clear context through examples and notes like 'series=true is not supported when metric="domains"', but lacks explicit when-not-to-use or 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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