marketing

name	marketing
description	Use when the user wants the complete marketing asset suite for a product in one run — "/marketing", "build all the marketing assets", "generate everything for the launch", "all the animations and brand assets for X". Not for a single asset (use that asset's own skill) and not for launch copywriting alone (use /launch).

Marketing Mega-Pipeline

One command produces a product's full asset suite: brand onboarding, UI polish, logo reveal, product demo, launch video with audio, social clips, and OG assets. The individual asset skills own their recipes; this skill owns sequencing, gates, and run state.

REQUIRED BACKGROUND: marketing-studio (engine-repo workflow shape and non-negotiables). All PLAYBOOK rules apply.

Resume check — before anything else

Glob out/*/marketing/run.json in the engine repo. If an incomplete run exists (any asset not delivered), this invocation is a RESUME: skip Phase 0, load the saved intake answers from the manifest, and continue at the first asset whose status is not approved/delivered. If several incomplete runs match, ask which one. Only a fresh run proceeds to Phase 0.

On resume, still run the Phase 1 environment checks (shared-repo guard + launch.py --check — the previous process died mid-flight), but skip brand onboarding and Phase 2 polish if the manifest marks them complete. Trust a rendered/approved status only after confirming its artifact actually exists on disk; missing or truncated artifact → demote that asset to planned.

Phase 0 — Intake: ONE batched question round, then silence

Fresh runs only. Ask everything in a single AskUserQuestion, then run without asking again (exceptions: per-asset stills gates in gated mode, final delivery):

1. Product/brand + destination — which brand, and where finished assets land in the product repo (default: its existing media/marketing dir).
2. UI polish before filming? Default YES: the demo films the real running app, so rough edges get rendered at 60fps forever. YES = impeccable → polish → frontend-verify on the product repo before any capture. NO = film as-is. This edits product code, so it is always the user's call — never silently skip it AND never silently do it.
3. Audio — music only / music + voiceover / none.
4. Social clips — platforms and count (default: X + LinkedIn, one each).
5. Checkpoint mode — full-auto (self-check stills, user reviews the final gallery) or gated (user approves stills before each full render).

Phase 1 — Foundation

1. Shared-repo guard + python launch.py --check (marketing-studio steps 0–1).
2. Brand: if brands/<id>.json is missing, onboard per PLAYBOOK. Brand-token judgment stays in the main loop — do not delegate it.
3. Create the run manifest out/<brand>/marketing/run.json. It stores BOTH the Phase 0 intake answers (brand, destination, polish flag, audio choice, social config, checkpoint mode) AND one entry per planned asset. Statuses mean exactly this:
   • planned — not rendered yet. Gated mode: user approves pre-render stills before the render starts (that is the ONLY user gate per asset).
   • rendered — artifact on disk, post-render frame check pending (extract 2–3 frames from the artifact and inspect them — self-check in both modes).
   • approved — frame check passed; approval is recorded in the manifest the moment it happens, never inferred from chat history. A resumed session redoes the frame check for any rendered asset, showing the frames to the user first in gated mode.
   • delivered — copied to the product repo. Update the manifest after every status change. Never restart a run from scratch because the session died.

Content approval gate. Once out/<brand>/marketing/brief.json is synthesized and passes node scripts/lint-copy.mjs, run node scripts/build-storyboard.mjs <brand> and show the user storyboard.html for content approval BEFORE any rendering; in full-auto mode the main-loop judge reviews it instead.

Brief synthesis rules. The zod schema (studio/src/lib/brief.ts) is the contract; fill the grounding sections, not just the copy: audience + customerLanguage + objections + switchingForces from the brief-inputs grounding, and a proofPoints entry (claim + source) for EVERY number the copy cites — an unsourced stat is fabrication, omit it instead (lint-copy WARNs on stat-shaped claims in a brief with no proofPoints). Draw hook.headline and each of the (up to two) altHeadlines from DIFFERENT hook categories per references/hook-formulas.md, record the categories in hook.strategies, and include at least one emotion-forward category (story/contrarian) against a value hook — evidence in references/campaign-evidence.md (read it before synthesis; it also lists debunked claims that must never appear in copy). Build cta with the [Action Verb] + [What They Get] formula. The storyboard renders the grounding sections so the approver can check copy against facts.

Copy council (full-auto mode). Before the main-loop judge accepts the storyboard, run a 3-judge council on the brief copy: three parallel Sonnet subagents (model: claude-sonnet-5, explicit), one per lens — positioning sharpness (would April Dunford sign it?), emotional resonance vs feature-dump, and evidence honesty (every claim traced to a proofPoint) — with the third judge additionally instructed to argue AGAINST shipping the copy (mandatory dissenter; kills the echo chamber). Issues raised by 2+ judges go back to synthesis; single-judge nits are noted, not blocking. In gated mode the human storyboard review replaces the council — offer it only if the user asks for a copy critique. (Pattern adapted from Corey Haines' marketing-council skill, MIT.)

Phase 2 — UI polish (only if opted in)

In the PRODUCT repo: impeccable → polish → frontend-verify. Must fully complete before Phase 3 — re-shooting every asset because the UI changed after capture doubles the run. Commit product-repo polish separately from asset delivery.

Phase 3 — Asset pipeline: STRICTLY SEQUENTIAL

The engine repo is shared mutable state (props builders, registries, render queue). Two asset skills at once collide and renders saturate the CPU. One asset at a time, in this order. (One blessed exception: /logo-reveal touches only the engine repo and captures nothing, so it may run concurrently with Phase 2 polish, which touches only the product repo — zero shared state, real wall-clock savings.)

#	Skill	Why this position
1	/logo-reveal	Cheapest comp — surfaces brand-token bugs before the expensive assets
2	/product-demo	Films the (now polished) UI; footage feeds everything downstream
3	/launch-video	Picture-lock the hero video (composes demo + logo + copy). Before locking, when the brief carries altHeadlines: node scripts/render-hook-variants.mjs <brand> renders the competing hook takes and registers them as Mission Control variants — pick the winner there, then lock. Optionally node scripts/render-variants.mjs <brand> logo-reveal for hero takes.
4	/audio-track	Score the locked launch video (music/VO per intake) and merge
5	/social-clip × N	Reuse demo/logo footage per platform; add stings if audio opted in
6	/og-assets	Statics + README GIF pulled from final footage

Per asset: stills gate before full render — node scripts/contact-sheet.mjs <brand> <Comp> is the standard gate artifact (each sub-skill enforces it), render logs | tail -2, then update the manifest. Assets #1 (/logo-reveal's Blender staging) and #2 (/product-demo's Playwright capture) check the content-hash footage cache first and skip the expensive stage when their inputs (product git state, capture/staging script, and resolved config) are byte-identical to the last run; pass --force to re-capture.

Phase 3.5 — Responsive export matrix. Once the launch video is picture-locked and the social clips are rendered, run node scripts/render-matrix.mjs <brand> to fan the launch video and social clips into all four aspects (16:9, 1:1, 4:5, 9:16) by responsive layout, not crops. Variants land in out/<brand>/matrix/ and register in the manifest's exports[]. Add --stills-only first to prove the layout with one still per aspect before committing CPU to full renders. The muted-autoplay rows (9:16 and 1:1) additionally emit an <id>-captioned variant with the VO burned into on-screen captions, and node scripts/build-captions.mjs <brand> writes matching launch.srt/launch.vtt sidecars — both require the brand's audio props (skipped silently without them).

Execution mode — pick by session model

• Opus or Sonnet session (default): run each asset skill inline in the main loop. Visual-tuning loops go to Sonnet subagents (model: claude-sonnet-5, always explicit) so iteration stills die with their context. Mechanical checks: Haiku or inline. Escalate to Fable at most once, standalone, only if a new template must be designed mid-run.
• Fable session (e.g. ultracode "/marketing" with Fable as the main model): executor-judge mode, below. Fable never executes asset recipes inline — its context grows for hours at judging-grade rates while doing checklist work.

Executor-judge mode (Fable session)

Fable is the judge and orchestrator; it holds only the intake answers, the manifest, dispatch prompts, and verdicts. Everything heavy happens in disposable executor contexts.

1. Brand onboarding stays in the main loop — one-time judgment work, exactly what Fable is for. If brands/<id>.json is missing, derive tokens from the product repo (DESIGN.md, tailwind, CSS vars per PLAYBOOK) and fold any underivable values into the Phase 0 intake batch — never a mid-run question to an absent user.
2. Phase 2, if opted in, goes to one claude-opus-4-8 executor that runs impeccable → polish → frontend-verify in the product repo and returns before/after screenshots plus the verify result as raw data. Fable judges those before any capture starts — the polish pass is heavy UI work and does not belong in the judge's context.
3. One executor subagent per asset, strictly sequential (the engine repo and CPU rules from Phase 3 apply unchanged). Models, always explicit: claude-opus-4-8 for /product-demo and /launch-video (capture choreography and copywriting need judgment); claude-sonnet-5 for /logo-reveal, /audio-track, /social-clip, /og-assets (recipe execution).
4. Dispatch prompt contract: tell the executor to read the asset's SKILL.md, the marketing-studio skill, and the PLAYBOOK gotchas before acting; give it the brand id, manifest path, and intake answers; have it execute the recipe through full render and return raw data — output path, 3 extracted still paths, and any deviations. No prose reports.
5. Judge protocol per asset: Fable Reads the returned stills and judges against the brand's voice rules, composition quality, and copy (no em dashes, no hype). Approve → manifest approved, next asset. Problems → send a numbered correction list via SendMessage to the SAME executor (its context is intact; never respawn a fresh executor to fix its own work). If the resume fails because the executor's transcript is gone (it happens), spawn a MINIMAL corrections executor whose prompt carries the complete defect list plus file-level context — never re-run the whole asset recipe. Maximum 3 correction rounds per asset; after that, record the asset as rendered with judge notes and move on — the user adjudicates it in the final gallery.
6. This mode is full-auto by definition — Fable replaces the per-asset user gates as a stronger judge. The user still sees the final gallery (Phase 5 is unchanged), and delivery + commits stay in the main loop.
7. Fable never spawns Fable, and the 3-Fable session cap applies. Executors are the fleet; the judge is singular.

Dynamic workflows — the only two uses

Whatever the execution mode, the Workflow tool touches only read-only fan-outs. Asset execution NEVER goes in a workflow: workflow agents run in the background with no channel back to the judge or the user, renders are CPU-bound and serial so fan-out buys zero wall-clock, and each fresh agent() re-reads the PLAYBOOK per call. Corrections need SendMessage to a live executor — a workflow can't do that. Mechanical single commands (smoke.mjs, file copies, manifest I/O) stay inline in Bash; a subagent spawned to run one command costs more than the command.

The two legitimate workflows, all agents Sonnet with model explicit:

1. Phase 4 brand-compliance sweep: parallel() one reviewer per asset still, each finding adversarially verified before it triggers a re-render.
2. Optional pre-delivery judge panel: 3 judges score the full gallery; only issues flagged by 2+ judges go back to Phase 3. In executor-judge mode this panel is a pre-filter — the panel flags, the Fable judge adjudicates.

Fable never goes inside a workflow (the model-guard hook blocks it in parallel()/pipeline() constructs anyway).

Phase 4 — Final QA

1. node scripts/smoke.mjs — must pass. 1b. Mechanical judges before any agent sweep (cheap, run all five): node scripts/judge-av-sync.mjs <brand> (VO overruns/caption dwell), node scripts/judge-demo-pacing.mjs <brand> (dead air), node scripts/judge-palette.mjs <brand> <still> (forbidden colors; low-confidence findings are product-UI suspects, treat per step 2's false-positive rule), node scripts/judge-motion.mjs <brand> (motion-craft conventions in studio src + brand motion-token bands), and node scripts/check-budgets.mjs <brand> (hard size gate — an OVER blocks delivery). Their JSON reports feed the judge; only findings the reports can't decide go to the agent sweep.
2. Brand-compliance sweep: one Sonnet subagent reviews a still from every asset against the brand's voice rules (e.g. noban: profit gold #d6c23c, never green). Re-render only violators — but VERIFY findings against the product repo's source first. Product screenshots inside assets show the PRODUCT's own fonts/tokens, not the engine brand's stand-ins; a reviewer expecting the engine's mono will misread the product's mono as a violation (paperroute run 2026-07-10: 4 of 5 sweep findings were this exact false positive; the fifth was a real product bug, fixed in the product repo, no asset re-render needed).

Phase 5 — Delivery

1. Copy every asset to the destination dir; write a README there listing each file and its intended use.
2. Launch the operator console: node scripts/mission-control.mjs <brand> (add --port N if 4600 is taken). Tell the user the URL it prints (default http://localhost:4600/). This is a live click-to-approve gallery reading out/<brand>/marketing/run.json — one card per asset with the embedded artifact, an Approve button, a Redo box, and variant pickers. An advisory bar under the header shows the mechanical judges' verdicts (expandable findings), footage-staleness warnings ("capture footage: N commits behind" — computed from the cache's recorded product git state), and engagement results when they exist. The run is not done until the user has seen the gallery.
3. While it runs, poll out/<brand>/marketing/run.json and out/<brand>/marketing/review.json for the operator's actions: an asset flipped to approved in the manifest is that asset's approval gate cleared (approve is the manifest gate, never inferred from chat); a redo entry in review.json — with its note, also stored as redoNote on the asset (now back to planned) — feeds the Phase 3 correction loop. Re-render the redone asset per its skill, update the manifest, and the console picks up the new state on its next 2s poll.

Phase 5.5 — Thumbnails and paste-ready post kits. Before delivery, run node scripts/extract-thumbs.mjs <brand> to grab one poster still per aspect from out/<brand>/matrix/ into out/<brand>/thumbs/, then node scripts/build-postkit.mjs <brand> to assemble out/<brand>/postkit/{x,linkedin,tiktok,shorts,youtube,instagram}/ — each folder gets the right-aspect video, thumbnail, a lint-gated caption.txt, alt.txt, caption sidecars (YouTube/LinkedIn), and a POST.md checklist. This is what makes delivery paste-ready instead of raw files the user has to reassemble by hand.

Phase 5.75 — Results loop (after publishing, usually a later session). When posts go live (via /launch or the launch-engine), record them in out/<brand>/marketing/posts.json — an array of {platform, url, variant?, metrics?} where variant is the run.json variant id the post carried (e.g. hook-2) and metrics is manual entry for platforms without API access (LinkedIn). Then node scripts/fetch-results.mjs <brand> pulls X engagement (X_BEARER_TOKEN in .env; exit 2 + unavailable markers without it) into results.json, and Mission Control shows engagement per hook variant. The winning hook CATEGORY feeds the next brief's hook.strategies pick — that closes the A/B loop with reality instead of taste.

Phase 6 — Close out

1. Commit the engine repo (tests + lint + smoke first; out/, assets/, studio/public/*/ stay uncommitted). An uncommitted engine tree strands the run.
2. Commit product-repo delivery.
3. Final summary: per-asset table (file, duration, status) + deviations log.

Red flags — stop and re-read this skill

• Running two asset skills concurrently "to save time" → engine-repo collision.
• Starting with /launch-video "because it matters most" → brand bugs found at the expensive end.
• Capturing before Phase 2 finished → everything gets re-shot.
• "Session died, start over" → read run.json and resume.
• Asking the user questions one at a time across the run → all questions live in Phase 0.
• Deciding yourself whether to edit the product's UI → that is intake question 2, the user's call.