FilmLab

Orbit Turnaround

lab_orbit

Create an asynchronous orbit turnaround from a project image or a public HTTPS image. To use your own picture, import it first with lab_add_media (art image) and pass the returned asset_key here. Costs credits without get_cost: quote the price first and wait for the person's confirmation, then pass max_credits. Never automatically retry a paid run. Pass job_id to poll the existing run; it takes precedence over starting and needs no project or image. The selected views are approximate angle estimates, unvalidated on AI characters.

Input Schema

Name	Required	Description
`job_id`	No	Existing orbit job id as a positive integer string; polls status and approximate views.
`get_cost`	No	Return the catalog price and current balance without starting or charging anything.
`asset_key`	No	The asset_key of an image imported into this project with lab_add_media (art image); give this OR startbild to start.
`startbild`	No	Address of an image owned by this project or a public HTTPS image; give this OR asset_key to start.
`project_id`	No	Project id as a positive integer string; required to start.
`max_credits`	No	Maximum credits confirmed by the person, as a nonnegative integer string; required to start.
`nur_eigene_daten`	No	Only for a model that sends inputs to China or a US recipient without a documented basis, when the step carries images, clips, voices or faces. Means: this material shows or contains no real person other than the human using this account. Set it ONLY after the human has said exactly that for THIS step; never assume it, never reuse it for the next step. Not needed when the human has declared this material in the FilmLab app: the backend reads that declaration, also for material derived from it; only the app can store one. An LK reference, a licensed likeness or another person's agreement does not replace it. Without it the backend refuses with drittland_dritte_gesperrt before any charge; then use a non-gated model or text only.

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedNov 6, 2026

changedInput schema / properties / nur_eigene_daten / description

Previous value: -"Only for a model that sends inputs to China or a US recipient without a documented basis, when the step carries images, clips, voices or faces. Means: this material shows or contains no real person other than the human using this account. Set it ONLY after the human has said exactly that for THIS step; never assume it, never reuse it for the next step. An LK reference, a licensed likeness or another person's agreement does not replace it. Without it the backend refuses with drittland_dritte_gesperrt before any charge; then use a non-gated model or text only."New value: +"Only for a model that sends inputs to China or a US recipient without a documented basis, when the step carries images, clips, voices or faces. Means: this material shows or contains no real person other than the human using this account. Set it ONLY after the human has said exactly that for THIS step; never assume it, never reuse it for the next step. Not needed when the human has declared this material in the FilmLab app: the backend reads that declaration, also for material derived from it; only the app can store one. An LK reference, a licensed likeness or another person's agreement does not replace it. Without it the backend refuses with drittland_dritte_gesperrt before any charge; then use a non-gated model or text only."

Changed1 schema field changedNov 6, 2026

addedInput schema / properties / nur_eigene_daten

Added value: +{
+  "description": "Only for a model that sends inputs to China or a US recipient without a documented basis, when the step carries images, clips, voices or faces. Means: this material shows or contains no real person other than the human using this account. Set it ONLY after the human has said exactly that for THIS step; never assume it, never reuse it for the next step. An LK reference, a licensed likeness or another person's agreement does not replace it. Without it the backend refuses with drittland_dritte_gesperrt before any charge; then use a non-gated model or text only.",
+  "type": "boolean"
+}

Changed2 schema fields changedOct 31, 2026

addedInput schema / properties / asset_key

Added value: +{
+  "description": "The asset_key of an image imported into this project with lab_add_media (art image); give this OR startbild to start.",
+  "type": "string"
+}

changedInput schema / properties / startbild / description

Previous value: -"Address of an image owned by this project or a public HTTPS image; required to start."New value: +"Address of an image owned by this project or a public HTTPS image; give this OR asset_key to start."

AddedOct 30, 2026

TDQS

A4.6/5.0

Behavior5/5

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

Annotations only declare non-read-only and non-destructive. The description adds substantial behavior: asynchronous execution, credit cost, mandatory price quote and confirmation, no automatic retries, job_id precedence, and a caveat that views are approximate/unvalidated on AI characters. This is strong disclosure beyond annotations.

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?

Front-loads the purpose and then adds only operational caveats. Each sentence carries distinct information (import path, cost handling, retry prohibition, polling precedence, quality caveat), with no filler.

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

Completeness4/5

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

Given seven optional parameters and no output schema, the description covers the main call paths and cost/quality behavior well. It omits explicit return-value description (though job_id polling implies a job id is returned) and leaves the complex nur_eigene_daten gate entirely to the schema, so it is strong but not fully complete.

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

Parameters4/5

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

Schema coverage is 100%, so the baseline is 3. The description adds workflow meaning for max_credits (quote then confirm) and job_id (takes precedence, needs no project/image), plus the asset_key import path. It does not elaborate on nur_eigene_daten, but the schema already documents it thoroughly.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb ('Create') and resource ('orbit turnaround'), scope ('from a project image or a public HTTPS image'), and distinguishes the import path by naming lab_add_media. The job_id polling mode is also clearly separated from starting a new run.

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

Usage Guidelines4/5

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

Gives explicit operational guidance: use lab_add_media before asset_key, call get_cost and obtain confirmation before max_credits, never auto-retry, and use job_id to poll rather than start. It does not explicitly compare this tool to other image-generation siblings (e.g., lab_neue_winkel) or state when not to use it, which keeps it from a 5.

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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