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Design & media
course-video-studio
Try itTurn finished lecture scripts into presenter-led course videos with lecture narration. This course video studio prepares the spoken narration for each lesson, then records a digital-teacher delivery, so enablement teams get ready-to-publish lecture videos and training presenter clips.
What it does
Turn finished lecture scripts and one authorized teacher portrait into lesson videos. Each lesson is narration first, then talking-head clips that fully contain the speech.
The skill document
Course Video Studio
Turn finished lecture scripts and one authorized teacher portrait into lesson videos. Each lesson is narration first, then talking-head clips that fully contain the speech.
Scope and adjacent routes
Use this Skill when a course or training team wants talking-head lesson videos from a stable portrait plus lecture text.
Route audio-only course work to course-narration-studio. Route a single
presenter clip to talking-avatar-video. Route a founder weekly update to
founder-ip-avatar-studio. Without authorization for the likeness and the
voice, stop at confirmation.
Inputs and defaults
The hard inputs are:
- one accessible teacher portrait;
- final lecture text for at least the pilot lesson;
- lesson order;
- likeness and voice rights;
- a pronunciation table whenever the lecture contains recurring names, terms, or acronyms.
If those terms exist and the table is empty, stop and collect the readings. Do not guess them. Final lecture text is the spoken source. A deck is useful only after the user extracts the spoken script; this Skill does not parse slides.
Reuse the frozen voice_id, language, and framing. Default to
model: "auto" for video and a source-derived aspect ratio. Split a
lesson into sequential containable clips when planned speech is longer
than the longest video duration that can hold it.
Golden path
-
Inspect the portrait. Record MIME type, width, height, aspect ratio, byte size, and whether it has an alpha channel. Build the lesson ledger. For a local portrait or sample, upload only through the bundled client after inspection. Never pass a local path to a remote tool.
-
Select or clone a teacher voice. A clone requires consent first; access to a file is not consent. A suitable sample is currently about 10 to 300 seconds, no larger than 20 MiB, and clean single-speaker speech. Use the live
voice_cloneadmission card before any cloneclient_request_idorbeatra.voices.clonecall: routevoice_clone, toolbeatra.voices.clone, live price for one successful activated voice, the provisional estimate, the 600-credit signup gift usually cannot start this clone,https://console.beatra.ai/topup, and starter ¥29 / 11,000 credits. Do not recommend ¥198. Do not createclient_request_idor submit until the user confirms they have topped up or already have enough credits. Do not offer a free clone. Submitbeatra.voices.cloneexactly once:{ "sample": {"type": "artifact", "artifact_id": "artifact_..."}, "display_name": "Course Teacher", "consent_attested": true, "model": "auto", "client_request_id": "opaque-course-video-clone" }Poll with
beatra.tasks.getuntil terminal, then freeze the returnedvoice_id. Without a clone, callbeatra.voices.listwhen a catalog voice still needs to be selected. Never put a display name invoice. -
Call
beatra.models.listfortext_to_speechandimage_to_video. Confirm the video route admits[image, driving_audio]. Compare the portrait's actual MIME, dimensions, byte size, and alpha-channel presence with every advertised image constraint. Read the longest video duration that can fully contain speech. Split the pilot lecture into sequential containable segments at sentence or section boundaries. Do not shorten the lecture to cheapen a clip. Do not ship a truncated lesson. Usemp3only when the live speech card supports it and the live video card acceptsaudio/mpeg. If the user requestedflac,opus, orpcmand the video route does not accept the resulting format, explain the incompatibility before any paid call and obtain the user's choice. Do not silently change the format. If any required media fact is unavailable or incompatible, stop before TTS. Keep each speechinputat or below 50,000 characters. -
Confirm the pilot speech card: script segments, voice, format, live estimate, and one
client_request_idperbeatra.speech.synthesizecall. Submit each segment once through the bundled client. Poll each narration task withbeatra.tasks.getuntil terminal. Read the returned artifact plus actualtask.output.audio.mime_type,duration_seconds, andsize_bytes. Approve the real audio before that segment's video. Never treat a script preview as an audio review. -
Refresh the
image_to_videocards and admit the actual portrait plus that segment's approved speech. Recheck every image and driving-audio fact. If terminal audio size remains unavailable, stop before video. Use the smallest supported integer video duration at or above the actual speech length. Show the video admission card beforebeatra.videos.animate: routeimage_to_video, toolbeatra.videos.animate, approved portrait and speech artifacts, prompt, audio-led duration, resolution if set, output count, provisional live estimate, the 600-credit gift usually cannot start this video,https://console.beatra.ai/topup, starter ¥29 / 11,000 credits. Do not recommend ¥198. Do not submit until the user confirms they have topped up or already have enough credits. Approved narration does not authorize the video call. Each segment video has its ownclient_request_id. -
After the pilot lesson's clips are accepted, repeat segment-narration-then-video for remaining lessons. Each paid stage has its own
client_request_id. Submit only through the bundledscripts/mcp_client.py. Do not configure a host Beatra Connector. Do not use REST/OpenAPI as a fallback. Poll every video task withbeatra.tasks.getuntil terminal. -
Deliver labeled lesson videos in teaching order, with segment order inside a lesson, plus actual dimensions, duration, usage, and
billing.net_charged_credits. Review identity, term readings, and lip timing.
Decisions that require confirmation
Confirm rights, the voice, the pilot, and every video admission card. A changed lecture is new narration and, if the audio changes, a new video.
Recovery
Recover each stage only with its identical frozen payload and ID. Recover
a lost task ID through beatra.tasks.list and beatra.tasks.get. On
insufficient_balance, 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
- Read Course video workflow for ledgers, admission cards, payloads, and review.
- Read Installation and authentication only when authorization needs attention.
- Read Installation registration for first-use registration.
- Read Tasks and results and Billing, errors, and recovery for task and billing facts.
- Read Bundled MCP Client diagnostics when the bundled client cannot connect.
- Read Automatic updates and safety for update controls.
- Read Uninstall and disconnect only when the user asks to remove the package.
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 the 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/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 generation. The automatic-update 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
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