Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add ucsandman/marketing-studio --skill marketinggit clone --depth 1 https://github.com/ucsandman/marketing-studioWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/ucsandman/marketing-studio/marketing)<a href="https://agentmods.dev/skills/ucsandman/marketing-studio/marketing"><img src="https://agentmods.dev/badge/skills/ucsandman/marketing-studio/marketing/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/ucsandman/marketing-studio/marketing"><img src="https://agentmods.dev/badge/skills/ucsandman/marketing-studio/marketing.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Excessive Agency · line 28 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00071 | $0.05022 |
| Opus 5.5 | $0.00028 | $0.02009 |
| Sonnet 5.5 | $0.00014 | $0.01004 |
| Haiku 4.5 | $0.00007 | $0.00502 |
Grade A, and why
marketing scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 197 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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):
- Product/brand — which brand and the explicit product repo used by
--project. - 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.
- 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). - Social clips — platforms and count (default: X + LinkedIn, one each).
- Checkpoint mode — full-auto (self-check stills, user reviews the final gallery) or gated (user approves stills before each full render).
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2mo ago Changed · +10 lines 6e7a2fea9599
- 2mo ago Changed · +44 lines b90e79647758
- 2mo ago Changed · +20 lines 4a1c65e6d952
- 2mo ago First seen · 123 lines · 71 tokens per session scan A 383ea015d882
marketing is a skill published in the GitHub repository ucsandman/marketing-studio (255 stars, last pushed 2mo ago), licensed MIT. It adds 71 tokens to every session and 5,022 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
marketing compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| marketingucsandman/marketing-studio | Skill | 255 | 2mo ago | MIT | A | 71 | Claude Code |
| saas-product-demo-videonoamdorr/saas-product-demo-video | Skill | 69 | yesterday | MIT | A | 130 | Claude Code |
| seedance-promptsideshowroberto/vfx-agent-toolkit | Skill | 17 | yesterday | MIT | A | 68 | Claude Code |
| ccvideoAmazingAng/ccvideo | Skill | 21 | 3mo ago | MIT | A | 59 | Claude Code, Codex |
| remotion-video-workflowshaom/infocard-video-skills | Skill | 4 | 7mo ago | MIT | A | 50 | Codex |
| html-ppt-zhangzara-coralnexu-io/open-design | Skill | 107k | today | Apache-2.0 | A | 55 | Claude Code, Codex |
| adscoreyhaines31/marketingskills | Skill | 59k | yesterday | MIT | A | 239 | Claude Code |