Discover available LoRA models by category (qwen, xfs, other) to select the right model for ComfyUI workflows. Filter results by category when needed.
Discover available LoRA models categorized by type (qwen, xfs, other).
| Name | Required | Description | Default |
|---|---|---|---|
| category | No | Filter by LoRA category (optional) |
Changes observed during successful MCP inspections.
v0.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. "Discover available" implies a read-only listing, which is useful, but it does not disclose whether the scan is cheap or expensive, whether results are paginated or complete, or what the entries contain.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
One front-loaded sentence with no filler. Minor redundancy in re-listing the enum values that the schema already declares, but nothing that wastes the reader's attention.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a one-optional-enum list tool with no output schema, the description covers the essential purpose. The only gap is what a returned LoRA entry looks like (name vs. path vs. id), which matters slightly more because there is no output schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% and the single parameter is an enum already documented in the schema. The description merely restates the same three category values, adding no semantics beyond what structured data provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
States a specific verb ("Discover") and resource ("LoRA models") plus the categorization axis (qwen, xfs, other). No sibling tool deals with LoRAs, so it is naturally distinguishable, but the description never explicitly differentiates itself from the workflow/job tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no statement of when to use this tool, when not to, or what alternatives exist. The only guidance is implicit in the word "available," leaving the agent to infer that this is a discovery/list operation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.