Checklist the per-video bar — engine/sim
82.2/100
quantitative quality · weights learn from your reviews (
engine.sim.memory review thread-minus-the-hype-W47-Thu good|bad)⚠ 6 flag(s) — not yet ship-ready: copy_genericlow_vo_coveragedead_airgeneric_scene · see docs/strategy/VIDEO-CHECKLIST.md
Composition comp · template family · expected output
9:16 Reelrendered1:1 Squarepending16:9 Widepending9:16 4Kpending1:1 4Kpending16:9 4KpendingGIF (SMS)pending
expected output: 1/7 rendered — same matrix the /media preview surfaces for this asset.
Composition layer × scene 5 scenes · 28.9s · 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 | hook | 0–5.0s | kinetic-build | icon·liquid-chrome | ♪ node_lock | The SEO shortcut: ask a chatbot for keywords and trust the list. on-screen: "AI does keyword research alone" |
expected on screen: black ground · icosa hero in the shared Signal Field · Signum leads · mark · kinetic-build · icon·liquid-chrome logo · caption bottom-left spec (the prompt): comp_id shared Signal Fieldvisual markshape icosaground blacktreatment liquid-chromemotion kinetic-buildpower laser-lockinstrument laser-trace→"AI does keyword research alone" | |||||||
| 2 |  matches intent DiffCard template | diff | 5.0–13.6s | crossfade-8f | icon·ember-fill | ♪ node_lock | What works: the model groups ideas by intent, then we check each one against real search volume. on-screen: Reality: pair it with real volume |
expected on screen: black ground · a DiffCard panel over a dimmed Signal Field · Signum leads · code · crossfade-8f · icon·ember-fill logo · caption bottom-left spec (the prompt): comp_id DiffCardvisual codeshape icosaground blacktreatment ember-fillmotion crossfade-8fpower morphinstrument morph→Reality: pair it with real volumecurate codeLines, lines | |||||||
| 3 |  matches intent NumberedList template | teach | 13.6–18.9s | kinetic-build | icon·wireframe | ♪ node_lock | The real cost of trusting an AI keyword list is months writing for terms nobody searches. on-screen: The cost: chasing zero traffic |
expected on screen: black ground · a NumberedList panel over a dimmed Signal Field · Signum leads · node-graph · kinetic-build · icon·wireframe logo · caption bottom-left spec (the prompt): comp_id NumberedListvisual node-graphshape icosaground blacktreatment wireframemotion kinetic-buildpower morphinstrument morph+laser→The cost: chasing zero trafficcurate items, nodes | |||||||
| 4 |  first render · fix pending SchematicCard templatedead_airgeneric_scene | proof | 18.9–23.9s | receipts-count | icon·white-knockout | ♪ node_lock | Minus the Hype |
expected on screen: black ground · a SchematicCard panel over a dimmed Signal Field · Signum leads · receipts · receipts-count · icon·white-knockout logo · caption bottom-left spec (the prompt): comp_id SchematicCardvisual receiptsshape icosaground blacktreatment white-knockoutmotion receipts-countpower receiptsinstrument spotlight→Minus the Hypecurate nodes, statsLabels | |||||||
| 5 |  first render · fix pending shared field signature-3ddead_airgeneric_scene | resolve | 23.9–28.9s | coalescence | icon·liquid-chrome | ♪ bed_out | Minus the Hype |
expected on screen: black ground · icosa hero in the shared Signal Field · Signum leads · coalescence · coalescence · icon·liquid-chrome logo · caption bottom-left spec (the prompt): comp_id shared Signal Fieldvisual coalescenceshape icosaground blacktreatment liquid-chromemotion coalescencepower coalescenceinstrument coalescence→Minus the Hype | |||||||
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)
tiktokThe SEO shortcut: ask a chatbot for keywords and trust the list. What works: the model groups ideas by intent, then we check each one against real search volume from an API. Trust the raw list and you spend months writing for terms nobody searches. (AI-assisted)
instagram"AI does keyword research"
The shortcut: trust the chatbot list.
The reality: pair it with real volume.
Model clusters by intent.
We check each term against real search data.
Else: months of zero traffic.
#SEO #keywords #contentmarketing #AI #search
linkedinThe SEO shortcut: ask a chatbot for keywords and trust the list it gives you. That is how you lose a quarter.
What works: let the model brainstorm and cluster ideas by search intent, then join that against actual search volume and difficulty from a real API. The model is good at ideas, not at knowing what people actually type.
Trust the raw list and you spend months writing for terms nobody searches.
x"AI does your keyword research."
Real move: let the model cluster by intent, then check every term against real search volume from an API. Trust the raw list = months writing for zero traffic. temerarii.xyz
facebookIt is tempting to ask a chatbot for keywords and just trust the list. Here is the better way: let the model cluster ideas by intent, then check each term against real search volume from an API. Otherwise you spend months writing for terms nobody searches. See the method at temerarii.xyz.
threadsThe SEO shortcut: ask a chatbot for keywords and trust the list.
What works: the model groups ideas by intent, then you check each one against real search volume from an API. The model is great at ideas, bad at knowing what people type. Trust the raw list and you write for months at zero traffic.
pinterestHow to do AI keyword research the right way: let the model brainstorm and cluster keywords by search intent, then validate every term against real search volume and difficulty from an API. Why trusting a raw AI keyword list leads to months of zero-traffic content. SEO strategy and content planning.
blueskyThe SEO shortcut: trust the chatbot keyword list. The real move: cluster by intent, then check each term against real search volume from an API. Skip it and you write for terms nobody searches.
youtubeTitle: AI Keyword Research: Pair the Model With Real Search Volume
The SEO shortcut is asking a chatbot for keywords and trusting the list. We show the real workflow: let the model brainstorm and cluster by intent, then join it against actual search volume and difficulty from a real API. Trust the raw list and you spend months writing for terms nobody searches. SEO, keyword research, content strategy. temerarii.xyz.