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get_top_loras

Read-onlyIdempotent

Retrieve popular LoRA models for specific AI image generation base models like SDXL or Flux, with filtering options for content type and sorting by download metrics.

Instructions

Get top LoRA models for a specific base model.

Find the most popular LoRAs for SDXL, Flux, Pony, Illustrious. Set nsfw=true to include NSFW LoRAs (requires API key).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
base_modelNoSDXL 1.0
periodNoMonth
sortNoMost Downloaded
limitNo
nsfwNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

Annotations already cover key behavioral traits: read-only, non-destructive, idempotent, and open-world. The description adds some context by mentioning the API key requirement for NSFW content and listing example base models, which helps clarify scope. However, it doesn't disclose other behavioral aspects like rate limits, pagination, or error conditions, leaving room for improvement despite the annotation coverage.

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 appropriately sized with three sentences that are front-loaded: the first states the core purpose, the second provides examples, and the third adds a key constraint. There's minimal redundancy, and each sentence adds value, though the second sentence could be more structured (e.g., using a list).

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?

Given the tool's moderate complexity (5 parameters, no enums) and rich annotations, the description is partially complete. It covers the purpose and some constraints but lacks details on parameter semantics and behavioral nuances. The presence of an output schema reduces the need to explain return values, but the description doesn't fully compensate for the low schema coverage, leaving gaps in understanding.

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

Parameters2/5

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

With 0% schema description coverage for 5 parameters, the description must compensate but falls short. It only explains the 'nsfw' parameter (requiring API key) and implies 'base_model' usage through examples, leaving 'period,' 'sort,' and 'limit' undocumented. This partial coverage doesn't adequately address the schema's gaps, making parameter understanding incomplete.

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 clearly states the tool's purpose: 'Get top LoRA models for a specific base model.' It specifies the verb ('Get'), resource ('top LoRA models'), and scope ('for a specific base model'), making the intent unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'get_top_checkpoints' or 'get_top_images,' which likely serve similar ranking functions for different resource types.

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

Usage Guidelines3/5

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

The description provides implied usage context by listing example base models (SDXL, Flux, Pony, Illustrious) and mentioning that 'nsfw=true' includes NSFW LoRAs with an API key requirement. However, it lacks explicit guidance on when to use this tool versus alternatives like 'search_models' or 'get_model,' and doesn't specify prerequisites or exclusions beyond the API key note.

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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