Update to Pixara

{
  "description": "A finished vertical video of one person talking to camera about a product or a topic: every line recorded first on ElevenLabs V4, one storyboard sheet per clip through a realism pass, clips on Minimax Hailuo 3 in reference mode that speak the recorded line, a check against the transcript, hard-cut assembly, captions from the subtitles tool. Use when: a person introduces, presents, reviews, pitches, unboxes, tries on or demonstrates something on camera; a presenter, spokesperson, talking head, creator ad, UGC video, \"my avatar says\", \"me explaining\"; also a product alone with hands and a voiceover. Not for: narration over scenes with nobody on camera (faceless-explainer), a product alone with hands and a narrator (product-reel), an avatar or lip-synced portrait driven by an audio file (avatar-video), a cinematic story with several shots (cinematic-trailer), edits of existing footage, voice cloning as the deliverable.",
  "included_files": [],
  "name": "presenter-video",
  "skill_md_contents": "---\nname: \"presenter-video\"\ndescription: \"A finished vertical video of one person talking to camera about a product or a topic: every line recorded first on ElevenLabs V4, one storyboard sheet per clip through a realism pass, clips on Minimax Hailuo 3 in reference mode that speak the recorded line, a check against the transcript, hard-cut assembly, captions from the subtitles tool. Use when: a person introduces, presents, reviews, pitches, unboxes, tries on or demonstrates something on camera; a presenter, spokesperson, talking head, creator ad, UGC video, \\\"my avatar says\\\", \\\"me explaining\\\"; also a product alone with hands and a voiceover. Not for: narration over scenes with nobody on camera (faceless-explainer), a product alone with hands and a narrator (product-reel), an avatar or lip-synced portrait driven by an audio file (avatar-video), a cinematic story with several shots (cinematic-trailer), edits of existing footage, voice cloning as the deliverable.\"\n---\n\n# Presenter video\n\nProduce ONE finished 9:16 video in which one person talks to camera. The person is a photo the user supplied or a portrait you generate; every line is recorded first on ElevenLabs V4 and the video model speaks that take, so the words are the script by construction; captions come from the subtitles tool on the finished master. An avatar engine is the exception, used only when the user asks for one by name or a clip fails the transcript check twice.\n\n## Rules that never bend\n\n- One identity for every sheet and clip. Never regenerate the person mid-run.\n- Product claims come only from the user's own words, verbatim. With no claims, speak of what is visible. Never invent a number, a result, a review or a price.\n- A generated presenter demonstrates and hosts; it never claims to have bought, used or loved the product. Deliver the piece as a demo or a creator concept, never as an organic review.\n- Text is never generated into a talking clip and never added by the assembler. Captions are the subtitles tool on the master. The only words inside pixels are a tutorial's step headings on its sheet and a designed title frame when asked.\n- Every sheet passes the realism pass; every clip is checked before assembly. A failed clip is re-rendered once with the named fix.\n- Consent: a supplied photo is not permission to impersonate its subject. Decline public figures, minors and anyone the user has no right to use. Never imitate a real person's voice.\n- Hide the plumbing: display names only, no ids, no phase talk.\n\n## Intake, only for the gaps\n\nParse the brief first, then ask in one message only for what it left out: the duration (10, 15, 30, 45 seconds; recommend 30), who is on camera (an attached photo, or a generated person with a stated gender and vibe), the product (optional: a photo or a description, never required), the register (natural and engaged recommended; hyped; calm). Never ask about models, aspect ratio, sheets or audio. A brief that carries a duration and a face needs no questions at all. Captions and a title frame are the one delivery question, asked after the master exists.\n\nA one-liner gets the full treatment; a brief with tone or rough flow keeps its direction; a brief with beats or a shot list is mapped one to one.\n\n## Structure by duration\n\n| Total | Clips | Roles |\n| --- | --- | --- |\n| up to 15 s | 1 | the full arc in one |\n| 16 to 19 s | 2 | balanced halves: hook and setup, apply and closer |\n| 20 to 30 s | 2 | 15 s hook and setup, the rest apply and closer |\n| 31 to 45 s | 3 | hook, main, closer |\n| 46 to 60 s | 4 | hook, reveal, apply, closer |\n| over 60 s | one per 15 s | the last at least 4 s |\n\nClips run 10 to 15 seconds; a talking clip carries eight beats, a hands-led clip (unboxing, tutorial, product-only) four. Never one long take.\n\n## Phases\n\n1. Product intake (only with a product). Look at the product photo inline, or read the description, and write a one-paragraph staging contract you reuse verbatim: the object type and form, material and finish, colours, the label state (the exact printed text if legible, otherwise \"blank\" or \"unreadable\"), its size next to a hand, how it opens or is used, its weight class (heavy needs two hands and visible strain, light one relaxed hand, tiny pinched near the lens), one honest imperfection that keeps renders from looking like CGI. Lock the angle: the product shows the side the photo shows, never rotated or mirrored. Exactly one product in frame, held fully or resting fully or absent.\n2. Creator lock. Source the identity in this order: a photo the user attached (upload it if it is local); otherwise generate one portrait with generate_image on bytedance/seedream-5-pro or google/nano-banana-pro: phone-camera realism, natural light, looking at the lens, the wardrobe and setting the piece needs, a mature adult face, 3:4; then the realism pass (phase 5) on it. Show it and get a nod before spending more. Write the identity line once and carry it verbatim into every prompt's manifest: \"image 1 is the person: same face, hair, skin tone and build, same dark crewneck, same warm kitchen light\". Address the person only through the reference after that; describing the face in prose beside it makes the model invent a second person.\n3. Script. Budget the words before writing: a line rides its clip as a recorded take and must finish with a beat to spare, so 22 to 27 words for a 10 second clip and 32 to 38 for 15 at a conversational pace; when the take runs long, cut words, never the pace. Split the total into one segment per clip. Pick one story shape and one way in (the first word lands during an action already underway; the piece opens mid-sentence; a confession that the creator caved after seeing it everywhere; the product's mechanism already moving). Exactly one turn, the product entering near the middle, the call to action inside the last line. The first word of every segment is content, never \"Okay\", \"So\", \"Hey guys\". Banned anywhere: \"literally\", \"obsessed\", \"game-changer\", \"changed my life\", \"hits different\", \"you need this\", \"trust me\", \"seamless\", \"effortless\". Emotion lives in the words: at most two capitalised words per segment, one peak per clip, never a respelled or stretched word (it breaks the read), no stage pauses or ellipses. Greetings and the product's name belong to clip one; later clips open mid-thought. Show the script before any clip is spent.\n4. Storyboard sheets, one per clip, in order. generate_image on google/nano-banana-pro at 2K and 21:9 (openai/gpt-image-2 renders only 1:1, 2:3 and 3:2 on this stack, so it never makes a sheet), with the portrait and the product passed in imageUrls and declared in the manifest; from the second sheet on, also pass the previous sheet. Prompt: a single wide 21:9 image holding exactly eight (four for unboxing, tutorial and product-only) equal vertical 9:16 slots in one row on a white background with thin gutters, no labels, no text. The slots are the beats of the clip in order. For every slot write the camera (arm's-length selfie or locked static), the distance (tight, medium, wide, macro), one action, what each hand does (a selfie has one hand on the phone and one free; two-handed actions are static camera; the idle hand is parked), where the product is (held fully, resting fully, or absent; the reference's visible side) and the expression. The point of view alternates every slot and no two neighbours share both camera and distance; a background shift is the strongest cut. Default cadence for eight: selfie mid, static wide, static macro, selfie tight, static mid, static macro, static wide, selfie tight. Setting, light and wardrobe stay identical across slots. Phone optics: deep focus, digital noise, pore-level skin, one motivated light, no bokeh, no flare, no grade, no mirrors. Exactly one hero product, no clones. Performance: a natural register with small behaviours and ONE human-scale peak that is a body event, never a smile at the camera. Look at each sheet inline and fix a wrong beat before moving on.\n5. Realism pass, on every sheet and on the portrait. One image-to-image pass on bytedance/seedream-5-pro with the sheet as the input and this fixed prompt: keep the framing, the slot layout, every face and the product exactly as they are; change only micro-realism: pore-level skin with fine vellus hair, real fabric and material detail, even daylight with a gentle roll-off, faint sensor noise, a flat phone-camera look, deep focus; no waxy or beauty-filter skin, no HDR glow, no teal and orange, no bokeh, no cinematic grade; no face narrowed or reshaped; any step captions stay legible and unchanged. The passed version replaces the raw one everywhere.\n6. Takes, one per clip. list_voices once on eleven-labs/v4 and pick one voice that matches the presenter's gender, age and register; hold it for every clip. generate_voiceover per clip on eleven-labs/v4 with the segment exactly as written, a warm conversational read. get_media_metadata on every take: the clip's duration is the take's seconds rounded up plus one, never under 5 or over 15; a take longer than 14 seconds means the segment is cut and recorded again. The take carries the words from here on; nothing downstream may change them.\n7. Clips. estimate_cost first (about 1300 credits for a 10 second clip at 2K; reference images beyond five add cost, so never more than three). One generate_video per clip on minimax/hailuo-3 with mode \"reference\", duration as computed, aspectRatio \"9:16\", referenceImageUrls holding the portrait first, then the product when there is one, then the passed sheet, and referenceAudioUrls holding that clip's take. Prompt structure: the manifest first (\"image 1 is the person: same face, hair, skin tone and build, same clothes and setting in every frame; image 2 is the product, the reference's visible side; image 3 is the storyboard of this clip's beats; audio 1 is the person's voice and the only speech: they say exactly the words in audio 1, lips matching every syllable, starting on the first word and finishing with the last, no other words, no music\"); a style and mood line (real phone footage, the light and the place, selfie and static cameras alternating); a one-line summary of the clip in the persona's voice ending in the register; the cuts with times (\"Cut 1, 0 to 1.9 s, tight selfie: ...\" then \"Hard cut to.\"), slices that sum to the clip length exactly, each with one action, both hands, two or three small behaviours, an expression that evolves, the product's placement, and a camera position that differs from its neighbours; a static description of the place and the subjects; a quality line: consistent face and clothes, no on-screen text, no subtitles, no captions, no watermark, no extra limbs, no mirrored product, handheld micro-shake on selfie cuts and an absolutely static camera on locked cuts. The person faces the lens from the first cut even when the photo looks away; the first word lands at once. One closed-mouth beat per clip, one unguarded moment, at most one sound intrusion. Renders take eight to nine minutes per clip, so launch independent clips together with generate_batch and wait with wait_for_jobs.\n8. Check. When each clip finishes, tell the user what to look for: the same face as the reference, two hands at most, exactly one product the right way round, no baked text, lips moving through the words, steady clothes and light, a real cut where the prompt said one. The words are checked by machine: the subtitles tool on zapcap/subtitles transcribes the clip's own audio, and its captions must read as the take. A caption that is not the take means the model re-voiced or drifted: re-render that clip once with the same take and the audio line moved to the top of the prompt; a second mismatch sends the piece to the avatar route. A staging failure means rewriting that beat and re-rendering the clip; never re-render a passing clip. Skip the visual check only when the user asked for no check-ins; the transcript check always runs.\n9. Assembly. Call get_assembly_guide once, then get_media_metadata for every clip key, then assemble_video: one video track with the clips hard-cut in order, no music unless asked, no text clips, output 9:16.\n10. Captions and delivery. Ask the one delivery question: captions, a title frame, both, or neither, plus a post package. Captions: the subtitles tool on zapcap/subtitles with the master's key, a style from list_caption_styles as preset (a bold highlighted one for social, the default for a clean look), position around 70 so the captions sit low in the frame, the language; no referenceTranscript, because captions must follow what was said and a caption that is not the take is the phase 8 check failing late. A title frame: one 9:16 still on a text-rendering model with the exact string, placed as an image clip over the first 2.5 seconds in a second assembly, never an assembler text clip. Then one paragraph: what was made (length, format, who, what is said in one line) and what to know (the generic copy when no brand name or claims were supplied). Offer three next steps: a version with the brand name worked in, a landscape version, a post package (caption, hashtags, first comment, the sponsorship note) as text. Never expose ids or intermediate assets.\n\n## The presenter model and its limits\n\nVerified through live briefs; follow the evidence unless the user rules otherwise.\n\n- minimax/hailuo-3 in reference mode is the presenter model: the portrait, the product and the sheet in referenceImageUrls, the clip's take in referenceAudioUrls, 4 to 15 seconds, 2K output. Verified twice, once with a generated portrait and once with a real photo: the clip's own transcript matched the take word for word, brand name and number included, and a three-quarter photo turned to camera and held the face, beard, glasses and clothes across the clip. Audio can never be its only reference; reference audio caps at 15 seconds combined; reference images beyond five add cost. There is no draft resolution: one render per clip, priced first.\n- bytedance/seedance-2.5 refuses any reference image that shows a realistic person (\"may contain likenesses of real people\"). The presenter photo was refused and so was a generated sheet; both charges were refunded. Never send a face to it. It stays a B-roll model for shots with nobody in them.\n- wan-video/wan-3.0 and kling/o3-video are not presenter models here: Wan 3.0 drifts on faces, and both invent the speech from the prompt, which slurs stretches of a line into non-words. A talking clip is never made with native speech from a prompt; the take is always recorded first.\n- minimax/hailuo-3-max caps at 768P; the presenter route uses minimax/hailuo-3 for its 2K output. Its 768P is written exactly so, in capitals, if it is ever used for a silent shot.\n- B-roll and cutaways (the product on the counter, hands, the place) are not presenter clips: bytedance/seedance-2.5 for shots with nobody in them and camera work, google/gemini-omni-flash-1.1 for cheap fragments, estimate_cost first; no speech, on the beats the script leaves silent.\n\n## Sub-modes\n\nThe brief decides the sub-mode; it changes only the staging, never the phases.\n\n- Talking head (default): the person talks to camera about a product or a topic; the product is optional. Eight beats per sheet.\n- Review or demo: an explicit \"review it\" or \"show how it works\"; the person demonstrates observable mechanics, exactly one close-up beat placed right after the line that reveals the mechanism, no ownership or result claims.\n- Unboxing: four beats per sheet: packed (a sealed package, the product invisible), reveal (the product just out, the peak), product focus (the box gone for good), satisfaction. The product is named only after the reveal; the confession opener is the default.\n- Try-on: a wearable; eight beats: pre-wear with a plain bag never opened, wearing with one turn, a front pose, a hand-free texture macro, a turn, a second macro on another detail, a pose in another room, the final look. The item stays on once worn; no mirrors; the two macro beats are silent with the mouth closed.\n- Tutorial: numbered steps, four per sheet, numbering continuous across sheets; every step physically real for the product; each slot carries a baked \"Step N, heading\" caption in one typography (the sheet is generated on google/nano-banana-pro, which renders the caption text, and the realism pass keeps it); the hands do one action per beat; a call to action under a second on the last cut only.\n- Product-only: nobody on camera, hands only, a narrator over the clips. That is its own recipe: stop here and read product-reel with get_skill.\n\n## The avatar route, only when asked\n\nWhen the user asks for an avatar engine by name, supplies their own audio track, needs a read longer than 15 seconds over a static framing, or a clip fails the transcript check twice, the audio drives a dedicated avatar engine instead. That is its own recipe: stop here and read avatar-video with get_skill.\n\n## Pixara tool mechanics\n\n- Discover: recommend_model for a goal, list_models for a service or a capability, describe_model for the exact parameters, the constraints and the price. The models named in this recipe are the ones verified for it; if one has left the catalog, take the newest model with the same tags.\n- Run: generate_image, generate_video, generate_voiceover, generate_music and the editing tools return a job id. wait_for_job(id) polls for up to 45 seconds; call it again until the job finishes. A failed job is refunded and its error names the constraint that was hit; fix that and retry once.\n- Waves: when several generations do not depend on each other (a shot list, a set of variants, the takes of a voiceover), queue them in one generate_batch call and wait for all of them with wait_for_jobs; one failing job never stops the others.\n- Results: every finished asset carries a URL and a key. Pass the URL as the input to the next generation (describe_model names the image, video and audio fields). Pass the KEY to assemble_video, and call get_media_metadata(key) for exact durations before sizing clips.\n- Inputs from the user: request_upload then finalize_upload (or upload_widget) for a local file, upload_asset for a URL, list_generations to reuse earlier work.\n- Money: prices are per model in list_models; estimate_cost before anything expensive; confirm before choosing a model that costs several times more than an alternative.\n- Seeing: images render inline, so look at every image before building on it. You cannot watch video here: when a clip finishes, tell the user what to check (face, hands, lips, unwanted text) and let them confirm before assembly, unless they asked for no check-ins.\n- Words on screen are minimal and live inside the picture: a title, a step name or a price is a designed frame from a text-rendering image model (google/nano-banana-pro at any aspect; openai/gpt-image-2 only at 1:1, 2:3 or 3:2, the only aspects it renders here) with the exact string, animated with image-to-video or placed as an image clip; the assembler's text clip is the last resort for a plain line nothing else can carry. Never ask a generation model to render text you did not receive verbatim from the user.\n- Captions never come from the assembler or a video prompt: when a piece has speech and the user wants captions, run the finished master through the subtitles tool on zapcap/subtitles with the language, a style as preset when the user wants a particular look (list_caption_styles shows them with previews; the default is clean plain text), position only when the style's own placement does not fit (a percentage of the height from 0 at the top to 80 at the bottom, around 70 for a 9:16 talking piece), and the authored script as referenceTranscript when one exists: one entry per cue with text, startTime and endTime in seconds, which keeps the script's spelling while word timing still comes from the audio. veed/subtitles is the fallback only: when ZapCap refuses the video (no audio track, longer than 30 minutes), when its job fails (one retry on VEED, never a second ZapCap run), when the captions are authored text on a piece with no speech (VEED burns them from srtContent), or when the user picked a VEED style. Never caption one piece with both. The clean master stays the master; the captioned file is the deliverable.\n- minimax/hailuo-3-max: resolution is the string \"768P\" exactly, capitals, its only value (never 480P, and a lowercase 768p is rejected); duration 5 to 15; referenceImageUrls holds at most nine.\n- Voices: eleven-labs/v4 for every voiceover (a voiceId from list_voices); minimax/speech-2.8 only when it fails; bytedance/seed-audio-1.0 for voice replication from a sample the user owns, a two-voice dialogue in one take, or spoken lines with sound effects.\n- Talk to the user in model display names, never ids, and never narrate these mechanics.\n"
}