Checklist the per-video bar — engine/sim
98.5/100
quantitative quality · weights learn from your reviews (
engine.sim.memory review social-W29-Sun-2 good|bad)⚠ 1 flag(s) — not yet ship-ready: copy_generic · see docs/strategy/VIDEO-CHECKLIST.md
Composition comp · template family · expected output
9:16 Reelpending1:1 Squarepending16:9 Widepending9:16 4Kpending1:1 4Kpending16:9 4KpendingGIF (SMS)pending
render pending — silent master not yet on disk
expected output: 0/7 rendered — same matrix the /media preview surfaces for this asset.
Composition layer × scene 9 scenes · 61.6s · comp_id + rendered still + tier + the script
| # | Layer (comp_id · still · tier) | Beat | Timecode | Motion | Logo | Audio | VO / on-screen / caption |
|---|---|---|---|---|---|---|---|
| 1 |  matches intent shared field signature-3d | open | 0–5.5s | spatial-parallax | icon·3d-extrude | ♪ bed_in | For years, social listening meant one person reading comments and calling it a trend. on-screen: Listening used to be guessing |
expected on screen: white ground · torus hero in the shared Signal Field · Nuntius leads · node-graph · spatial-parallax · icon·3d-extrude logo · caption bottom-left spec (the prompt): comp_id shared Signal Fieldvisual node-graphshape torusground whitetreatment 3d-extrudemotion spatial-parallaxpower summoninstrument summon→Listening used to be guessing | |||||||
| 2 |  matches intent shared field signature-3d | hook | 5.5–11.4s | kinetic-build | icon·color | ♪ node_lock | Your next campaign is sitting in plain sight inside what people already say about you. on-screen: Your audience already told you |
expected on screen: white ground · torus hero in the shared Signal Field · Nuntius leads · mark · kinetic-build · icon·color logo · caption bottom-left spec (the prompt): comp_id shared Signal Fieldvisual markshape torusground whitetreatment colormotion kinetic-buildpower laser-lockinstrument laser-trace→Your audience already told you | |||||||
| 3 |  matches intent NumberedList template | teach | 11.4–18.7s | kinetic-build | icon·color | ♪ node_lock | We pull mentions through a search API, then run each one past a model that tags mood and topic. on-screen: Pull mentions with an API |
expected on screen: white ground · a NumberedList panel over a dimmed Signal Field · Nuntius leads · node-graph · kinetic-build · icon·color logo · caption bottom-left spec (the prompt): comp_id NumberedListvisual node-graphshape torusground whitetreatment colormotion kinetic-buildpower morphinstrument morph+laser→Pull mentions with an APIcurate items, nodes | |||||||
| 4 |  matches intent ComparisonTable template | proof | 18.7–26.0s | receipts-count | icon·color | ♪ node_lock | Now you can see, in one view, what people praise, what annoys them, and what they wish you sold. on-screen: Tag mood and topic at scale |
expected on screen: white ground · a ComparisonTable panel over a dimmed Signal Field · Nuntius leads · receipts · receipts-count · icon·color logo · caption bottom-left spec (the prompt): comp_id ComparisonTablevisual receiptsshape torusground whitetreatment colormotion receipts-countpower receiptsinstrument spotlight→Tag mood and topic at scalecurate colA, colB, rows, statsLabels | |||||||
| 5 |  matches intent CodeWindow template | diff | 26.0–33.3s | crossfade-8f | icon·color | ♪ node_lock | The Big T-M does not chase one loud comment. We act on the pattern under a thousand of them. on-screen: We sell the pattern, not the noise |
expected on screen: white ground · a CodeWindow panel over a dimmed Signal Field · Nuntius leads · code · crossfade-8f · icon·color logo · caption bottom-left spec (the prompt): comp_id CodeWindowvisual codeshape torusground whitetreatment colormotion crossfade-8fpower morphinstrument morph→We sell the pattern, not the noisecurate codeLines, windowTitle | |||||||
| 6 |  matches intent ChecklistCard template | teach | 33.3–41.4s | kinetic-build | icon·color | ♪ node_lock | Feed the tagged complaints back to a model and ask it to group them into the three things to fix first. on-screen: Turn complaints into a roadmap |
expected on screen: white ground · a ChecklistCard panel over a dimmed Signal Field · Nuntius leads · node-graph · kinetic-build · icon·color logo · caption bottom-left spec (the prompt): comp_id ChecklistCardvisual node-graphshape torusground whitetreatment colormotion kinetic-buildpower morphinstrument morph+laser→Turn complaints into a roadmapcurate items, nodes | |||||||
| 7 |  matches intent KpiGrid template | proof | 41.4–48.0s | receipts-count | icon·color | ♪ node_lock | Three clear fixes beat thirty scattered opinions, and you can show exactly where each one came from. on-screen: Three fixes beat thirty opinions |
expected on screen: white ground · a KpiGrid panel over a dimmed Signal Field · Nuntius leads · receipts · receipts-count · icon·color logo · caption bottom-left spec (the prompt): comp_id KpiGridvisual receiptsshape torusground whitetreatment colormotion receipts-countpower receiptsinstrument spotlight→Three fixes beat thirty opinionscurate kpis, statsLabels | |||||||
| 8 |  matches intent LegacyCard template | step | 48.0–55.3s | kinetic-build | icon·color | ♪ node_lock | Try it: pull your mentions, tag mood and topic, group the pain, and ship the top three this month. on-screen: Do this: pull, tag, group, act |
expected on screen: white ground · a LegacyCard panel over a dimmed Signal Field · Nuntius leads · pipeline · kinetic-build · icon·color logo · caption bottom-left spec (the prompt): comp_id LegacyCardvisual pipelineshape torusground whitetreatment colormotion kinetic-buildpower throwinstrument laser-trace→Do this: pull, tag, group, actcurate stages, steps | |||||||
| 9 |  matches intent shared field signature-3d | resolve | 55.3–61.599999999999994s | coalescence | icon·3d-extrude | ♪ bed_out | The future of brand work listens before it speaks, because the audience already wrote the brief. on-screen: The future listens first |
expected on screen: white ground · torus hero in the shared Signal Field · Nuntius leads · coalescence · coalescence · icon·3d-extrude logo · caption bottom-left spec (the prompt): comp_id shared Signal Fieldvisual coalescenceshape torusground whitetreatment 3d-extrudemotion coalescencepower coalescenceinstrument coalescence→The future listens first | |||||||
Format stack 3 aspects · same scenes[], re-cropped
9:16
1080×1920
Stories · TikTok · YouTube Shorts · Reels
1:1
1080×1080
LinkedIn · Facebook · Instagram
16:9
1920×1080
X/Twitter · YouTube · LinkedIn video
Channels 9 destinations
LinkedInX/TwitterYouTubeInstagramFacebookThreadsTikTokPinterestBluesky
Social captions supplemental published copy · per channel (comp_id level)
tiktokYour next campaign is already written in your comments (AI-assisted method): pull mentions via a search API, tag each for mood + topic, group the pain into 3 fixes, ship those this month. Act on the pattern, not one loud comment. #socialllistening #aimarketing #strategy
instagramYour audience already wrote the brief.
Pull mentions. Tag mood + topic.
Group the pain into 3 fixes.
Ship those first.
Listen before you speak.
#sociallistening #marketing #aitools #brandstrategy #data
linkedinSocial listening, done with receipts. Instead of one person reading comments and calling it a trend, we pull mentions through a search API, tag each for mood and topic with a model, then group the complaints into the three things to fix first. Three clear fixes beat thirty scattered opinions, and you can trace each one back to its source. The audience already wrote the brief; the job is to read it honestly.
xSocial listening used to be one person reading comments. Now: pull mentions via API, tag mood + topic, group the pain into 3 fixes, ship those. Act on the pattern, not the loudest comment.
facebookYour next campaign is sitting inside what people already say about you. We pull mentions through a search API, tag each for mood and topic, then group the complaints into the three things to fix first. Three fixes beat thirty opinions. Want the full method? It's in the video.
threadsYour next campaign is already in your comments. Pull mentions via a search API, tag each for mood + topic, group the pain into 3 fixes, ship those this month. The audience already wrote the brief.
pinterestSocial listening strategy: brand mention tracking, sentiment analysis with AI, audience insights, customer feedback grouping, marketing roadmap, voice of customer, social media monitoring. Turn scattered comments into three clear fixes you can ship this month.
blueskySocial listening: pull mentions via API, tag mood + topic, group the pain into 3 fixes, ship those. Act on the pattern, not one loud comment.
youtubeSocial Listening: Your Audience Already Wrote the Brief
For years social listening meant one person reading comments and calling it a trend. Here's the honest method: pull mentions through a search API, run each past a model that tags mood and topic, then group the complaints into the three things to fix first. Three clear fixes beat thirty scattered opinions, and you can show exactly where each came from. Listen before you speak. AI-assisted, human-judged.