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create_traffic_matching_list

Define network traffic rules by creating a traffic matching list on a UniFi site with host, site, and list type, name, and items.

Instructions

Create a new traffic matching list on a site.

host: console name, ID, or composite ID (MAC:numericId format). site: site name or ID. Validated locally before the request (a missing field raises ValueError naming it): a top-level type — the discriminator the controller validates first (verified live: an empty body is rejected with Missing $.type value; observed value: 'PORTS'). traffic_list: for a PORTS list the live object also carries name (str) and items (list). Note: the list field is 'items', not 'entries'.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
hostYes
siteYes
traffic_listYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Install Server

TDQS

A4.4/5.0
Behavior4/5

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

With no annotations, the description carries the transparency burden and does substantial work: it discloses local validation, ValueError behavior on missing fields, the required `type` discriminator, a live-verified rejection message, and the 'items' vs 'entries' naming trap. It does not cover authorization or side effects, but the disclosed behavior is unusually rich.

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 front-loaded with the core purpose and then uses compact labeled details for host, site, validation behavior, and traffic_list structure. It is slightly dense, but every sentence contributes useful information and there is no fluff.

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?

For a nested-object create tool with 0% schema coverage, the description covers the essential call requirements: host/site identifiers, the `type` discriminator, the PORTS object fields, and the items/entries gotcha. The output schema exists, so return-value details are not required. Minor ambiguity remains about whether other `type` values besides 'PORTS' are supported, but the description is otherwise sufficient.

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 0%, so the description must compensate fully. It explains host formats (console name, ID, or composite ID), site naming, the required top-level `type` discriminator, and the PORTS-list shape with `name` and `items`. This adds meaning far beyond the bare schema with `additionalProperties: true`.

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 opens with a specific verb and resource: 'Create a new traffic matching list on a site.' This clearly distinguishes it from sibling read/update/delete operations and identifies the scope (a site).

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?

The description clearly indicates this is for creating a new traffic matching list, which implies when to use it versus listing, updating, or deleting. It does not explicitly name alternatives or exclusion criteria, but the 'create' framing provides clear context.

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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