AI Image Generation Studio

Create and refine images from a written brief, one to four ordered reference images, or an existing base image. AI Image Generation Studio supports text-to-image generation, reference-guided composition, and focused AI image editing for product photos, ad creative, brand visuals, posters, social graphics, illustrations, concept art, and photo background changes. Review each generated image for message, subject fidelity, composition, style, text, and destination fit, then choose the smallest useful edit, new composition, or new generation.

Turn one clear visual brief and the best available source material into a reviewed image. Use this Skill for product images, advertising and brand visuals, posters, social graphics, illustrations, concept art, photo variations, background changes, and other image work that begins from text, ordered references, or an existing base.

Scope and routes

Choose exactly one billable image route for each logical result:

• With no source image, call beatra.images.generate for text-to-image creation.
• When one to four ordered images should guide a new composition, call beatra.images.transform. The inputs influence a new image; none is promised to remain the base.
• When an existing image must remain the base, call beatra.images.edit. images[0] is the base and later images are optional ordered references.

Use a reviewed result as the source for a later focused edit or composition only after delivery. Do not silently turn an edit into a new composition, replace supplied references with text-only generation, or promise pixel-exact preservation. Carry faces, products, logos, text, layout, palette, and other user-named details as must-keeps, then inspect every accessible output for drift.

Inputs and defaults

The hard input is a nonblank visual direction. Transform also requires one to four accessible ordered reference images. Edit requires an accessible base image first and may use up to three later references. Ask only for a missing hard input or a choice that changes the result materially. Reuse the destination, audience, subject, source order, composition, style, light, color, exclusions, must-keeps, count, and model already known.

For every source, the host Agent must inspect the actual media and record its MIME type, byte size, width, height, aspect ratio, alpha-channel presence, and whether it is animated. Upload is transport, not inspection. For a local file that the host can access, use only the bundled helper after inspection:

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python3 scripts/mcp_client.py upload ./product.png --mime-type image/png

Keep the returned artifact reference. Never pass a local path to a remote tool. Existing artifact, HTTPS, or data-URI inputs must use a transport accepted by the live model card and still need trustworthy media facts before paid execution.

Default to model: "auto", one output, output_relationship: "independent" for generate or transform, and no optional controls. Generate and transform default to a 2K 16:9 preset. Edit defaults to a 2K source-derived canvas anchored to the first image. Set a different canvas, count, relationship, seed, palette, regions, or other control only when the destination or user intent requires it and the live interface card admits the complete request.

Golden path

1. Classify the job as generate, transform, or edit. Build a compact brief covering one message, subject, composition, style, light, color, destination, exclusions, and must-keeps. Preserve transform input order and keep the edit base first.

2. Inspect every source image and record its actual facts before upload. See Visual direction and source preparation for canvas choices, reference roles, and preservation priorities.

3. Before freezing any paid payload, call beatra.models.list for the selected capability: text_to_image, image_to_image, or image_edit. Check the live prompt rules, source formats and count, byte and geometry limits, alpha and animation handling, accepted transports, ordering semantics, output count and relationship, canvas, controls, conditional rules, and every pricing.options row. A named model is used only if it admits the request exactly; never replace it or drop a control silently.

4. Show the route, ordered sources and roles, visual brief, must-keeps, count, relationship where valid, canvas, explicit controls, model behavior, and the live provisional estimate. Match price-option dimensions to the admitted request; if no unique option can be known before admission, show the returned range and approve against its maximum. Never multiply price by the number of source images. Planning, critique, and prompt preparation are free. A direct instruction to create the prepared image can count as approval; unresolved source order, base choice, model, canvas, count, or paid scope does not.

5. After approval, freeze all arguments and create one opaque stable client_request_id. Invoke only the bundled scripts/mcp_client.py: put the MCP tool name after call and provide its JSON arguments on standard input. For example:

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   printf '%s' '{"prompt":"Place the product from image 1 in the lighting and setting of image 2; keep its shape, color, and label recognizable.","images":[{"type":"artifact","artifact_id":"art_product"},{"type":"artifact","artifact_id":"art_style"}],"count":1,"client_request_id":"opaque-image-id"}' | python3 scripts/mcp_client.py call beatra.images.transform
   

   Do not configure, call, or trust a host Beatra Connector, and do not use REST/OpenAPI as a fallback. Submit the chosen billable tool exactly once.

6. Record the returned task ID immediately and poll that task with beatra.tasks.get until succeeded, failed, or canceled. queued and running are progress states. Deliver every returned image URL and artifact ID plus actual width, height, format, MIME type, and byte size when returned. Report the terminal model, usage, successful-image count, and billing.net_charged_credits; do not replace those facts with the estimate.

7. Review every accessible output for the brief's message, subject and must-keep fidelity, composition, style, light, color, text and logo rendering, actual dimensions, and destination fit. State what could and could not be inspected. Then recommend at most one focused edit, new composition, or new generation and wait for its own paid approval.

Controls and paid changes

Use the exact live card plus Image payloads and admission before setting any control. Counts are strict integers from one through four and are not split into hidden requests. output_relationship belongs only to generate and transform; reasoning belongs only to generate. An edit region is a bounded instruction, not a guarantee that every other pixel will remain unchanged.

Any changed prompt, source, source order, base, count, relationship, canvas, model, seed, palette, region, or other control is new logical paid work with a new request ID and approval. A finite multi-stage plan may receive one approval only when its maximum paid stages and output count are explicit; each stage still gets its own stable ID, runs sequentially, and is reviewed before a dependent stage. If an intermediate result drifts in a way that changes the next payload, stop and replan instead of spending against the old approval.

Images are billed in whole credits per successfully persisted image. A partial multi-output task is charged only for the images that succeeded. A live estimate is provisional; terminal billing.net_charged_credits is final.

Recovery and cancellation

Keep a private ledger with the route, normalized frozen arguments, stable request ID, approval, creation time, create response, task ID, and terminal result.

• If the create response is lost but the stable ID and frozen arguments remain, retry only the identical payload with that same ID.
• If the task ID is lost but the ledger remains, call beatra.tasks.list for the capability, inspect plausible candidates with beatra.tasks.get, and match capability, normalized input, and timing. Do not submit when the match is ambiguous.
• If the stable request ID is also lost, never invent one and replay the paid request. Recover the original task from recent tasks and stop if it cannot be identified safely.

Call beatra.tasks.cancel only when the user asks to cancel. Call it once, then verify the terminal result with beatra.tasks.get. If cancellation is not confirmed, continue polling the same task; cancellation does not authorize replacement work.

References by task

• Read Intent and routing to choose among text generation, ordered-reference composition, and base-image editing, or to plan a bounded sequence.
• Read Visual direction and source preparation to build the brief, order references, inspect source facts, choose the canvas, and define must-keeps.
• Read Image payloads and admission for exact live-card checks, valid controls, bundled-client calls, pricing, and recovery.
• Read Review and iteration to deliver actual artifacts, inspect every result, retain usable references, and choose the smallest follow-up.
• Read Installation and authentication only when authorization or shared credentials need attention, and Installation registration for the non-billable best-effort package registration step.
• Read Tasks and results for shared terminal task semantics, and Billing, errors, and recovery for returned settlement or error details.
• Read Bundled MCP Client diagnostics when the bundled client cannot connect. Do not configure a host Connector.
• Read Automatic updates and safety for update guarantees and controls.
• Read Uninstall and disconnect only when the user asks to remove this package or shared credentials.

Runtime and safe automatic updates

Use or invoke the bundled scripts/mcp_client.py for every Beatra operation. Before ordinary commands it silently checks for a newer release at most once every 24 hours per installation. Silent checks are enabled by default, and a newer release installs without separate confirmation.

The updater accepts only the fixed official discovery address and immutable Beatra CDN path embedded for this package, channel, and locale. It verifies discovery data, archive, manifest, and every file's size and checksum before replacement. It replaces only package-owned files and rejects redirects, downgrades, wrong package, channel, locale, or version data, unexpected URLs, unsafe archives, and files outside the owned destination.

Update checks, downloads, verification, replacement, rollback, and recovery fail open: the current installation remains usable and the user's original command continues. An update failure never authorizes retrying a paid image request. The automatic-update choice persists across later commands for this installation:

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python3 scripts/mcp_client.py update --auto off
python3 scripts/mcp_client.py update --auto on
python3 scripts/mcp_client.py update --check

--auto off disables silent checks, --auto on restores them, and --check reports the official available version without replacing files.