Spoken Seeding Video Maker

Spoken Seeding Video Maker

Start from a topic and end with a spoken recommendation video. Nothing has to be uploaded — no product photo, no footage, no recorded voice.

Scope and adjacent routes

The route is: a subject, a script pattern, a shot list, generated beat frames, and one narrated vertical clip animated from the opening frame. It fits when someone wants to recommend something on camera-style video and has nothing shot yet.

When material already exists, another workflow fits better. A product photo that should become the video belongs in a product-video workflow. A finished script that only needs a voice belongs in a voiceover workflow. A reference clip to rebuild belongs in a teardown-and-remake workflow. A person or avatar who should appear on screen belongs in a talking-avatar workflow. Claims that need experience evidence stay at a labelled draft when that evidence is missing. Work that needs live-action footage or an editor is routed out. This package already has stills, narration, an optional music bed, and opening-frame animation, so a zero-footage short stays here.

Inputs and defaults

The one hard input is the subject: the product, service, or topic being recommended, in one line. Ask for it if it is missing; ask for nothing else up front.

Reuse whatever the conversation already states about the audience, the goal, the account's persona, and the destination platform. When those are absent, choose them from the subject and name the choice in the confirmation rather than asking.

Default to a 9:16 vertical canvas, a 12-second target, the script pattern selected in choosing the pattern, an opening frame plus any beats the user marks, and a narration voice matched to short social content. Music is off unless asked for. Default to writing the first 3 seconds as the hook — the reason to keep watching — rather than opening with a self-introduction.

Two facts shape every decision. The finished clip runs at most 15 seconds, and only the opening frame is animated into it — the other marked frames are delivered as stills for the user's own edit.

Claims split by source. What the subject is, who it is for, and how it is used are yours to write. Prices, specifications, ingredients, results, timeframes, certifications, and promotional terms come from the user. When those are missing, write the beat around them; never produce a plausible figure, because the user is the one who answers for it.

Golden path

Stages 1 to 3 cost nothing. No paid call happens before the user has approved the shot list.

1. Choose the pattern. Read the subject and select one of the six script patterns in choosing the pattern. The pattern sets the beat count and what each beat does.
2. Write the shot list. The spoken structure is hook → evidence or experience → call to action, each with second-level in and out points and two separate fields — what is on screen, and what is said. Screen the copy as described in writing the spoken lines. If the first 3 seconds do not carry the hook, revise that still-free shot list before any generation confirmation.
3. Show the shot list and get it approved. This is what the rest of the run is built from, and it is free to revise.
4. Read the live text_to_image, text_to_speech, and image_to_video cards with beatra.models.list — plus text_to_music when a bed was requested — and check every planned image, speech, video, and music fact against the relevant card.
5. Confirm preparation. Show which beats become frames, the 9:16 canvas and what changing it later would cost, the selected ready voice from beatra.voices.list, whether a music bed is included, the current estimate, and a stable request ID for every planned paid call.
6. Generate the beat frames with beatra.images.generate, one call per frame. Synthesize the narration with beatra.speech.synthesize, then read the actual returned duration, size, and MIME type. Produce the music bed with beatra.music.generate only when it was confirmed.
7. Show the real materials. Display the frames and play the narration whenever the host can access them, and report the true duration. Distinguish returned task facts from media the host could not inspect.
8. Show the video admission card. Show route image_to_video, tool beatra.videos.animate, approved opening frame, narration, audio-led duration (smallest whole second at or above the real narration length), resolution if set, provisional live estimate, the fact that the 600-credit signup gift usually cannot start this video, the exact URL https://console.beatra.ai/topup, and starter ¥29 / 11,000 credits. Do not recommend ¥198. Planning, comparison, or “make the clip” is not approval. Approved frames or narration do not authorize the video. Do not create a video client_request_id or submit until the user confirms they have topped up or already have enough credits for this estimate. Then call beatra.videos.animate once with the approved opening frame, the narration, an explicitly selected model, and that audio-led duration.
9. Poll that task with beatra.tasks.get until terminal, deliver the clip, and review what you can actually see.

Select the video model explicitly rather than leaving it to auto: only some models on this capability accept supplied narration, and one that does not will discard it.

The canvas is decided by the opening frame, so choosing it late means producing every paid artifact again.

Decisions that require confirmation

Confirm before spending in two stages: first the frame set, the narration, and any music bed together with every one of their priced calls, then the final video. The video confirmation comes after the user has seen the accessible frames and heard the narration, because that call costs the most.

Also confirm, rather than deciding alone: a canvas other than 9:16, a target length at the 15-second ceiling, a claim about the subject the user has not verified, adding the music bed, and any change after an artifact is approved. Each changed argument is new paid work with a new request identifier and fresh approval.

The music bed is delivered as its own audio track for the user to lay under the clip in their editor. Its length is arrangement direction inside the prompt rather than a control, so report the returned duration and expect trimming. Say both when it is confirmed, so its role is clear before it is paid for.

Execution

Invoke every remote Beatra tool only through the bundled scripts/mcp_client.py, with the tool name as the CLI argument and its arguments as JSON on standard input:

printf '%s' '{"capability":"text_to_image"}' | python3 scripts/mcp_client.py call beatra.models.list
printf '%s' '{"capability":"text_to_speech"}' | python3 scripts/mcp_client.py call beatra.models.list
printf '%s' '{"capability":"image_to_video"}' | python3 scripts/mcp_client.py call beatra.models.list
printf '%s' '{"capability":"text_to_music"}' | python3 scripts/mcp_client.py call beatra.models.list
printf '%s' '{"language":"zh-CN"}' | python3 scripts/mcp_client.py call beatra.voices.list

Do not configure or call a host Beatra Connector, and do not use REST/OpenAPI as a fallback. Give each logical paid request one stable opaque client_request_id and submit it exactly once.

Delivery and review

Deliver the selected pattern, the shot list, every frame as a delivered still, the narration, any music bed with its returned duration, the finished clip, each task ID, the returned artifact links, the resolved model, the returned dimensions and duration, and billing.net_charged_credits. Report only facts the task actually returned.

When the host can view or play the returned media, check that each frame matches the beat it was written for, that the narration is present and finishes cleanly, and that the clip fits the canvas. State which media details could not be inspected instead of inferring them from task metadata.

Recovery

Record each task ID immediately and poll only that task. queued and running mean wait. If a create response is lost, resubmit only the identical frozen payload under the same identifier; if a task ID is lost, list tasks for that capability and match candidates against your own ledger before any retry. Redoing one frame reuses the other artifacts unchanged. On insufficient_balance, relay the returned message, keep https://console.beatra.ai/topup exact, and retry the same frozen client_request_id only after the user says they have topped up.

References by task

• Selecting among the six patterns, setting the beat count, and naming what each beat does: choosing the pattern
• Writing spoken lines to a length budget, sourcing claims, and screening the copy: writing the spoken lines
• Exact payloads, what each confirmation freezes, polling, redoing one stage, recovery, and cancellation: seeding video workflow
• First install or expired authorization: installation and authentication
• Non-billable package registration: installation registration
• Task polling, artifacts, and result fields: tasks and results
• Balance, validation, and structured errors: billing, errors, and recovery
• When the bundled client cannot connect: Bundled MCP Client diagnostics
• Update guarantees and controls: automatic updates and safety
• Removing the package or shared credentials: uninstall and disconnect

Runtime and safe automatic updates

The bundled client silently checks for a newer release at most once every 24 hours per installation. When a higher version is available it installs automatically without separate confirmation. It downloads only from the fixed official Beatra discovery and immutable CDN paths for this package, channel, and locale, verifies the discovery data, archive, manifest, and every file's size and checksum before replacement, and replaces only package-owned files. It rejects redirects, downgrades, mismatched package, channel, locale, or version data, unexpected URLs, unsafe archives, and any file outside the owned destination.

Update checks, downloads, verification, replacement, and rollback all fail open: the current installation stays usable and the original command continues. An update failure never authorizes retrying a paid generation. The choice persists across later commands for this installation.

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. See automatic updates and safety.