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amanharshx
by amanharshx

export_create

Export a model to a specified format by creating an export job. Confirm the cost to proceed.

Instructions

Create a model export job (state-changing, may cost credits). Requires confirm_cost=true.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
halfNo
imgszNo
modelYesModel id, or slug when project is also provided.
formatYesRequested export format.
dynamicNo
projectNo
gpu_typeNo
confirm_costNoMust be true to allow a credit-costing export job.
Behavior3/5

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

Annotations already indicate the tool is not read-only, not idempotent, and not destructive. The description adds that it is state-changing and may cost credits, which is useful context beyond annotations. However, it doesn't disclose other behavioral traits like return format or additional side effects.

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 a single sentence of 13 words with no fluff. Every word adds value: 'create', 'model export job', 'state-changing', 'may cost credits', 'Requires confirm_cost=true'. It is front-loaded with the core action.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Despite having 8 parameters and no output schema, the description is very brief. It doesn't explain what happens after creating the export job, how to monitor progress (sibling tool export_status exists but not mentioned), or what the response contains. The tool is moderately complex, but the description omits essential context.

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?

Schema description coverage is low (38%), and the description only mentions confirm_cost. It does not explain the meaning or constraints of other parameters like half, imgsz, dynamic, gpu_type, etc. The description fails to compensate for the low schema coverage, leaving many parameters underspecified.

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 verb 'create' and resource 'model export job'. It distinguishes from sibling tools like 'dataset_export' by specifying 'model export', though it doesn't explicitly name the sibling. The purpose is clear but could be more explicit about the resource type.

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 notes that the tool is state-changing, may cost credits, and requires confirm_cost=true. It implies when to use (when export is needed and cost is acceptable) but provides no explicit guidance on when not to use or alternatives (e.g., dataset_export for dataset exports). The requirement for confirm_cost is a helpful constraint.

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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