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jellyfin_create_collection

Creates a Jellyfin BoxSet from a list of movie references, resolving each ID or title and only saving the collection when every reference is matched.

Instructions

Create a curated collection (BoxSet) from a list of movie references.

movies accepts a mixed list of tmdbIds, Jellyfin ids (or unique prefixes) and approximate titles; each is resolved and, in a dry-run, shown as matched / ambiguous / not found. Ambiguous or unknown references are NEVER guessed. With confirm=False (default) nothing is written. With confirm=True the collection is created only if EVERY reference resolved, so a partial collection is never created silently. Set overview to also write (and lock) a description on the new collection.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYes
moviesYes
confirmNo
overviewNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

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

No annotations are provided, so the description carries full burden. It comprehensively discloses behavioral traits: references are resolved and shown as matched/ambiguous/not found; ambiguous references are never guessed; with confirm=False nothing is written; with confirm=True creation only occurs if all references resolve; and overview can be written and locked. This is highly transparent and trustworthy.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise and well-structured: first sentence states the core purpose, followed by a paragraph explaining the movies parameter behavior and the confirm/overview logic. Every sentence adds information without fluff. It is front-loaded with the main action.

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 creation tool with 4 parameters and no annotations, the description covers behavior thoroughly. It explains parameter resolution, safety, and the overview lock. However, it does not mention prerequisites (e.g., authentication, permissions) or what the response contains (but output schema exists). Still, it provides enough context for an agent to use it correctly.

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 has 0% description coverage, so description must compensate. It explains movies in detail (accepts mixed ids and titles, resolution process), confirm (default false, only creates if all resolved), and overview (write and lock description). The name parameter is not described beyond being required, but its purpose is clear from context. Overall, significant value added over bare schema.

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 explicitly states it creates a curated collection (BoxSet) from movie references. This clearly distinguishes it from siblings like jellyfin_add_to_collection (adds to existing) and jellyfin_delete_collection (deletes). The verb 'create' and resource 'collection (BoxSet)' are specific and unique.

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 provides clear usage context: it explains the dry-run behavior with ambiguous/unknown references, the safety mechanism of confirm flag, and the condition for creation. While it doesn't explicitly state when not to use or name alternatives, the context of sibling tools and the detailed behavior give strong implicit guidance.

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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