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create_smart_collection

Create a filter-based Plex collection that auto-updates using criteria like genre, year, rating, or actor. Specify filters, sort order, content type, and limit for dynamic media grouping.

Instructions

Create a smart (filter-based) collection that auto-updates.

library_name: exact library name (e.g. "Movies"). title: name for the collection. filters: dict of field/value pairs with optional operators. Operators are appended to the key: ">>" = greater than, "<<" = less than, "!" = not. Examples: {"genre": "Action"} -- genre is Action {"year>>": 2000} -- year greater than 2000 {"genre!": "Horror"} -- genre is not Horror {"genre": "Action", "year>>": 2000} -- both conditions Common fields: genre, year, decade, rating, audienceRating, contentRating, resolution, studio, label, director, actor. libtype: content type to filter (required for show libraries). "movie", "show", "episode", "season", "artist", "album", "track". sort: sort order (e.g. "titleSort", "year:desc", "rating:desc"). limit: max items (0 = unlimited).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
library_nameYes
titleYes
filtersYes
libtypeNo
sortNo
limitNo
Behavior2/5

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

With no annotations, the description should disclose side effects, idempotency, and permissions. It explains filter behavior well but omits whether creation overwrites existing collections or requires specific permissions.

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 concise and front-loaded with the purpose, but the examples for filters take up space. Overall efficient and well-structured.

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?

The description covers parameters thoroughly but does not mention the return value (e.g., collection ID or success flag) and lacks error handling details. Given no output schema, this is a gap.

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 compensates fully: each parameter is explained with examples, operators, and common values, especially the filters parameter with detailed operator syntax and examples.

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 creates a smart (filter-based) collection that auto-updates, distinguishing it from sibling tool create_collection which likely creates static collections.

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 implies when to use this tool (for dynamic, filter-based collections) but does not explicitly contrast with create_collection or give when-not-to-use conditions.

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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