quote_generationUse before generate_3d_model so the user knows the cost: the credits a text or image run charges at a density. Read-only, spends nothing.
| Name | Required | Description | Default |
|---|---|---|---|
| mode | Yes | ||
| density | No | standard |
| Name | Required | Description | Default |
|---|---|---|---|
| mode | Yes | ||
| quote | Yes | Credits the run will charge | |
| density | Yes |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / $schemaPrevious value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"Output schema / $schemaPrevious value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and non-destructive behavior, and the description reinforces this with 'Read-only, spends nothing.' It adds useful behavioral context beyond annotations by explaining that this is a preflight cost check and that credits depend on mode and density.
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?
Two compact sentences with no filler. The key instruction 'Use before generate_3d_model' is front-loaded, and the rest of the description explains cost and safety without redundant restating of schema fields.
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 low-complexity quote tool with an output schema and strong annotations, the description covers what it does, when to call it, the meaning of its parameters, and its non-destructive nature. The only minor gap is not distinguishing it from other pricing/plan-related siblings, such as get_plans.
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 0%, so the description must compensate. It does: mode is mapped to 'text or image' and density is tied to the credit charge. This adds domain meaning beyond the raw enum values, though it doesn't detail relative costs for each density.
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 states a clear purpose with a specific verb and resource: quote the credit cost of a Generate run before generating. It differentiates the tool from generate_3d_model and explains the input scope (text/image run at a density), so an agent can understand what this tool does at a glance.
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 description explicitly says to use it before generate_3d_model so the user knows the cost, giving a concrete trigger condition. It does not explicitly exclude alternatives like get_plans or other pricing-related tools, which keeps it just short of full 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.
Most tools target distinct resources, but several overlapping pairs exist: search/list_projects both find projects by title, fetch/get_project both return project details, and upload_logo_image/request_logo_image_upload are two upload paths. The descriptions help clarify boundaries, but an agent could still misselect.
Tool names overwhelmingly follow a clear verb_noun snake_case pattern (create_, list_, get_, update_, delete_). Minor deviations like bare 'fetch' and 'search', plus the mixed '3d' in generate_3d_model vs '3D' in descriptions, keep it from being perfectly consistent.
At 31 tools, this exceeds the 25+ threshold where agent tool selection becomes cognitively heavy. While the server covers a broad platform, several tools are near-redundant and could be consolidated, making the count feel inflated.
The surface covers project lifecycle, sharing/publishing, AI generation, uploads, materials, and account/plan management quite thoroughly. Minor gaps exist, such as no direct create_coin_project tool and no deletion for generation runs, but these are workable.