FREE, no key needed: sample ULTRA LoRA actor cards (multi-pose stills) and object/set LoRA renders, and product spec sheets — see the quality before ordering anything.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the behavioral burden and does disclose no-auth access and zero cost. It also clarifies the content returned. It does not mention output format, limits, or delivery mechanics, but for a zero-parameter free-sample tool the stated behaviors are the material ones.
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?
The description is one front-loaded sentence with no filler. It leads with the most important facts, enumerates the sample categories, and closes with the usage intent.
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 no-parameter tool with no annotations and no output schema, the description covers access requirements, cost, and the substance of what the user receives. It could be more explicit about delivery format or sample limitations, so it is not a perfect 5.
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?
The input schema is empty, so there are no parameter semantics to document; baseline 4 applies. The description reinforces that no key is required and introduces no conflicting parameter expectations.
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?
The description opens with 'FREE, no key needed' and names the exact deliverable types: 'ULTRA LoRA actor cards (multi-pose stills)', 'object/set LoRA renders', and 'product spec sheets'. It clearly identifies the tool as a free sampling endpoint and distinguishes it from ordering, quoting, or top-up siblings.
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?
The phrase 'see the quality before ordering anything' tells the agent when to use this tool, and 'FREE, no key needed' communicates the access context. It does not explicitly name alternatives or state when not to use it, so it stops short of full routing guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool targets a distinct action: balance vs topup are check/add credit, quote vs order are estimate/purchase, and job_status/choose_actor_face/capabilities each serve a unique workflow step. There is no meaningful overlap between any two tools.
All tools share the inkflow_ snake_case prefix, but the set mixes bare noun endpoints (balance, capabilities, job_status, free_samples) with imperative verb phrases (order, quote, topup, sell_your_lora, train_ultra_lora_actor). This is readable but not a consistent verb_noun convention.
Ten tools is well within the ideal 3-15 range, and each tool earns its place by covering a distinct part of the platform: account, catalogue, quoting, ordering, status, samples, actor training, and marketplace selling. The scope matches the server's purpose without bloat.
The core lifecycle is well covered: discover capabilities, get a quote, place an order, top up credit, and monitor progress. Minor gaps exist such as order history/cancellation and marketplace listing management, but agents can work around these for the primary workflows.