Agent skill

Marketing

by ucsandman in ucsandman/marketing-studio

A skill your agent uses 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…

MITAuto-check passedMedia & Creative

Install Marketing

skills CLI
$ npx skills add ucsandman/marketing-studio --skill marketing -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install ucsandman/marketing-studio marketing --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/ucsandman/marketing-studio.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/marketing .claude/skills/marketing && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
marketing
GitHub stars
251
Token cost
~5.5k tokens
SKILL.md length
3,117 words
Files
3 (incl. references)
Skills in repo
13
Repo updated
First seen
Licence
MIT

At a glance

A skill your agent uses 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…

  • Works in 7 steps: Intake: ONE batched question round, then… → Foundation → UI polish (only if opted in) → …
  • The user wants the complete marketing asset suite for a product in one run — /marketing
  • SKILL.md covers Resume check — before anything…, Phase 0 — Intake: ONE batched…, Phase 1 — Foundation and Phase 2 — UI polish (only if…, plus 8 more sections
  • Calls node and python

What it does

Marketing is an agent skill from ucsandman/marketing-studio. 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).

Its SKILL.md is about 5.5k tokens, which your agent loads only when the skill is triggered. The skill folder holds 3 other files, including reference files (for example `references/campaign-evidence.md` and `references/hook-formulas.md`).

It sits in Media & Creative, covering Logo and visual identity and Copywriting. The repository describes itself as: Create product launch assets with Remotion, then review and distribute them through guarded, dry-run-first workflows. The licence is MIT.

When your agent uses it

  • 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

Example prompts

  • “/marketing”
  • “build all the marketing assets”
  • “generate everything for the launch”
  • “/marketing”

Requirements

  • Python 3

Workflow steps

7 steps, taken from the step headings in SKILL.md.

  1. Intake: ONE batched question round, then silence
  2. Foundation
  3. UI polish (only if opted in)
  4. Asset pipeline: STRICTLY SEQUENTIAL
  5. Final QA
  6. Delivery
  7. Close out

What it can do on your machine

Read from SKILL.md and the folder at commit 66cd1c3. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • node
    • python

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Marketing loads about 5.5k tokens when it runs, and up to ~7.8k if it reads all its reference files. Until then it costs about 83 tokens; SKILL.md has 3,117 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~83
When it runs · the whole SKILL.md, loaded when a task matches
~5.5k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~7.8k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from ucsandman/marketing-studio at commit 66cd1c3, republished under its MIT licence (© ucsandman). 3,117 words, ~5,451 tokens.

Download SKILL.mdSave it as .claude/skills/marketing/SKILL.md (or your agent's skills folder). This skill also uses 2 other files; get the full folder from GitHub.
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.

Production route: read docs/production-quality.md. Require --project <product-repo> and use <workspace> = <product>/marketing/assets/<brand>. Every generated capture, audio file, prop, public-stage asset, render, report, matrix row, and post kit stays in that product workspace. Engine-local out/ is not a product-run path.

Resume check — before anything else

Read <workspace>/marketing/run.json. If it exists and any asset is not delivered, this invocation is a RESUME: load its intake and continue at the first incomplete asset. Confirm every claimed artifact exists inside the product workspace before trusting state.

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 — which brand and the explicit product repo used by --project.
  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 + voiceover is the default and the only thing a film ships with; ask only WHO narrates (brand voice id vs default) and whether music leads or narration leads. "None" is not an option and music-only is a recorded exception (--music-only), never a default: a film with no voice explaining the product is not done (CLAUDE.md, learned 2026-09-01).
  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), then node scripts/install-skills.mjs --check — it warns when a bundled skills/ copy and its installed ~/.claude/skills copy have drifted, so the run does not follow a stale checklist. Warn only; fix the drift or note it, then continue.
  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 <workspace>/marketing/run.json. It stores the intake answers 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. In executor-judge mode the judge writes rendered plus the artifact path the moment an executor returns, before judging: the truckside session died on 2026-09-05 with a finished, scored launch film on disk and a manifest that still read planned, and the resume had to be reconstructed from file timestamps.
  4. Infographic bridge: build the product-owned <workspace>/marketing/infographic-style.md, then name it when an infographic is part of this run so that asset uses the approved brand tokens.

Content and direction gate. Once <workspace>/marketing/brief.json is synthesized and passes the copy gate, generate direction, shot plan, and production plan with the product-aware builder. Run node scripts/build-storyboard.mjs <brand> --project <product>. Approve the grounded copy and a style frame, then build an audio-bearing animatic with scratch voice/music and obtain named non-author approval before full rendering.

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.)

#SkillWhy this position
1/logo-revealCheapest comp — surfaces brand-token bugs before the expensive assets
2/product-demoFilms the (now polished) UI; footage feeds everything downstream
3/launch-videoBuild the chosen direction through an authored shot plan. Use directed LaunchVideo or a bespoke film according to the idea; captured UI, rebuilt UI, 2D, 3D, and hybrid shots are all valid. Picture, narration, music, and SFX share the same plan.
4/audio-trackMANDATORY unless the recorded music-only exception applies. Score the lock from product-owned audio inputs with --project <product>, verify the delivered master, and set the launch artifact to that scored file. A silent launch card is a defect, not a variant.
5/social-clip × NReuse approved sources per platform. Every delivered clip is scored in the product workspace before it counts. Muted-autoplay captions do not grant permission to ship a silent media file.
6/og-assetsStatics + README GIF pulled from final footage
7CardsOne stat card per brief proofPoint plus a quote card from the hook, rendered into <workspace>/marketing/cards/; skip when there is no grounded brief. A proof point with no figure is engineering-grounding prose, not a card — pass --skip-figureless to drop it instead of rendering it as a quote card. Footers never print a path or code citation: build-cards.mjs routes every source through displaySource, which prints the citation only when it reads as a plain human line and otherwise prints "Verified in the <brand> source".

Per asset, inspect inexpensive representative stills before a full render. For the hero film, generate hash-bound start/middle/end samples for every planned shot from the exact final render with contact-sheet.mjs --project <product> --plan ... --render .... Footage caches also live in the product workspace; --force re-captures only when needed.

Render budget: one full-resolution render per asset. The renderer is not where a two-hour run goes; correction rounds are. Measured 2026-09-01 on the 24-core box: a full-res LaunchVideo render is ~9 minutes and --x264-preset barely moves it (Chrome frame rendering is the bottleneck, not encoding), while --scale=0.5 renders 3.3x faster. So: judge every round from the contact sheet, and when a round needs motion, render the preview at --scale=0.5 as launch-vN-preview.mp4. The full-res render happens ONCE, after the stills pass. The postflop launch step rendered three full passes (27 minutes of the step's 48); this rule makes that one. A product bug found mid-capture is a note in run.json judgeNotes for the user, not a fix inside the run (postflop's demo step spent 64 minutes that way).

Budget the VO before you dispatch #4, not after. Picture-lock (#3) and audio (#4) are separate steps, and the trap between them is that measured VO word timings DERIVE act lengths, so scoring a locked film can push it past the 30-90s band launchTiming.test.ts enforces. Do the arithmetic yourself at dispatch time and hand it to the executor: frames_available = 2700 - current_total, minus the demo act which is FIXED (the PLAYBOOK forbids shortening a recorded demonstration to fit narration). Estimate each act's need at ~150wpm plus VO_LEAD + VO_PAD. If the narration overruns, say so in the brief and name the act to cut hardest — copy is trimmed ONLY in build-<brand>-audio.mjs, never by editing act constants. Measured on the practicalsystems run (2026-08-17): an 80.8s lock left 276 frames of headroom against ~564 needed, so ~25 words had to go. Name any claim that must survive the trim, because the shortest phrasing is often the false one — "cold outreach never sends without a human" compresses to "nothing sends without a human", which was untrue there.

Phase 3.5 — Responsive export matrix. After the scored launch and social clips pass their own review, run render-matrix <brand> --project <product> --production --stills-only to prove all formats. This is non-delivery layout evidence. Then run the production matrix without --stills-only; it binds each complete row to the approved plan and strict evidence. Use --verify-production to recheck pending existing media without rerendering it.

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.
Show full SKILL.md (1,329 more words)Show less

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-5 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-5 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. Watch the entire scored hero film with sound as a viewer before reading judge scores. Record whether you would share it and a concrete defect list; weak work returns to its cheapest responsible stage. Contact sheets cannot make this decision. 1a. node scripts/smoke.mjs — runtime gate; it is not visual approval. 1b. node scripts/check-audio.mjs <brand> --project <product> — HARD gate: every delivery-surface video carries its intended mastered track. Run it again after postkit. 1c. Run the existing A/V sync, pacing, palette, motion, drift, and budget judges with --project <product> where supported. judge-audio is mandatory reading, not optional: the sound-design judge's PASS counts VO lines from the manifest, while judge-audio transcribes the master and is the only check that proves each line was heard. On truckside (2026-09-06) the scored film passed the sound-design judge with a music bed whose outro fell inside the picture, which left 3s of dead air and an unheard line that only judge-audio caught. Read its content, order and trailing-silence lines before approving the audio track. These measure properties; warnings return to the perceptual review rather than becoming invented aesthetic thresholds. 1d. Record the structured non-author review in Mission Control, then run judge-production <brand> --project <product> --plan <production-plan.json> --render <final.mp4> --strict. Missing or stale stage approval, three-per-shot evidence, full render/audio attestations, or hash bindings blocks delivery.
  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. Assets already live in the product workspace; do not copy an engine-local render into place at the end. Write a product-owned README listing each file and intended use.
  2. Launch node scripts/mission-control.mjs <brand> --project <product> and give the user its local URL. First re-run contact-sheet on the hero master if any matrix row's judge ran after it: every judge-production run overwrites production-evidence.json, and the console binds the perceptual review to whatever render the evidence names last (truckside 2026-09-06: it pointed at a rejected 9:16 row until the sheet was regenerated). The run is not done until a named non-author has watched the scored film and the structured review is bound to current evidence.
  3. Poll <workspace>/marketing/{run,review}.json for approve/redo actions. Approval is a recorded, hash-bound action, never inferred from chat. A redo returns to the responsible stage and produces a new version rather than overwriting evidence.

Phase 5.5 — Thumbnails and paste-ready post kits. Extract thumbnails from the product-owned matrix, then run node scripts/build-postkit.mjs <brand> --project <product> --production. It copies only strict-PASS, hash-bound matrix assets and keeps captions, alt text, checklists, licences, and disclosures beside the media.

Phase 5.75 — Results loop (after publishing, usually a later session). /launch previews by default and takes the product-owned post kit. Live posting remains a separate explicitly authorized action. Record live URLs and later metrics in <workspace>/marketing/posts.json; feed the winning hook category into the next brief rather than treating one campaign's visual treatment as a permanent template.

Phase 5.9 — Prove the link preview actually changed. After delivery and site redeploy, compare the live og:image/twitter:image against the delivered product-owned OG file. A correct render does not prove the deployed meta tags or CDN are current.

Phase 6 — Close out

  1. Commit engine source changes only when this run required them (tests + lint + smoke first); generated run data stays in the product repo.
  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.
  • A second full-res render of the same asset before its stills passed → the render budget above; preview at --scale=0.5.
  • Fixing the product mid-run because the capture exposed a bug → note it, keep filming.
  • 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.

© ucsandman, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 2 other files (references) in skills/marketing of ucsandman/marketing-studio.

  • SKILL.md
  • references/campaign-evidence.md
  • references/hook-formulas.md

Open the folder on GitHubat commit 66cd1c3

Compare with similar skills

Marketing next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Marketing compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Marketing this skillucsandman/marketing-studio251—~5.5kAutomated safety check: PassMIT
Xhs Visual Directorziguishian/xhs-visual-director-skill1.4k—~2.2kAutomated safety check: PassMIT
Opentraces MarketingJayFarei/opentraces100—~2.3kAutomated safety check: PassCustom licence
Product Meaning ExtractorAnastasiyaW/codex-claude-code-config154—~2.7kAutomated safety check: PassMIT
Youtube Viral Optimizerinfranodus/skills119—~3.6kAutomated safety check: PassNone
Brand Onboardingstevenflanagan1/social-ai-team244—~2.9kAutomated safety check: PassNone

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Questions about Marketing

What does Marketing do?

A skill your agent uses 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…. Marketing is an agent skill from ucsandman/marketing-studio. 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".

When should I use Marketing?

Marketing fits situations like: 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.

How do I install Marketing in Claude Code?

Run `npx skills add ucsandman/marketing-studio --skill marketing -a claude-code`. Or copy the skill folder (skills/marketing in ucsandman/marketing-studio) into .claude/skills/marketing in your project. Claude Code loads it when a task matches its description.

How do I install Marketing in Codex?

Run `npx skills add ucsandman/marketing-studio --skill marketing -a codex`. Or copy the skill folder (skills/marketing in ucsandman/marketing-studio) into .agents/skills/marketing in your project. Codex loads it when a task matches its description.

Can I use Marketing in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add ucsandman/marketing-studio --skill marketing -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/marketing, .gemini/skills/marketing, .github/skills/marketing and .opencode/skills/marketing in your project.

What does Marketing need to run?

Going by SKILL.md and its folder, Marketing needs the command-line tools its instructions call (node and python). Our summary lists: Python 3.

Does Marketing access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Marketing safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Marketing use?

Marketing is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Marketing use?

About 5.5k tokens (SKILL.md is roughly 22k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 2.3k tokens, read only when the agent opens those files.

What are the alternatives to Marketing?

Skills that share tags, products or a category with Marketing: Xhs Visual Director (ziguishian/xhs-visual-director-skill, 1.4k stars), Opentraces Marketing (JayFarei/opentraces, 100 stars), Product Meaning Extractor (AnastasiyaW/codex-claude-code-config, 154 stars) and Youtube Viral Optimizer (infranodus/skills, 119 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Marketing?

ucsandman (a GitHub user) maintains it in ucsandman/marketing-studio, which has 251 GitHub stars. The repository holds 13 skills in this directory. The repository was last updated on September 6, 2026.

Source: ucsandman/marketing-studio on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.