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 product-demogit 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/product-demo)<a href="https://agentmods.dev/skills/ucsandman/marketing-studio/product-demo"><img src="https://agentmods.dev/badge/skills/ucsandman/marketing-studio/product-demo/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/product-demo"><img src="https://agentmods.dev/badge/skills/ucsandman/marketing-studio/product-demo.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 MCP Rug Pull · line 28 npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.Fix: Pin the version: npx @scope/[email protected]
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 | $0.00050 | $0.00510 |
| Opus 5 | $0.00025 | $0.00255 |
| Sonnet 5 | $0.00010 | $0.00102 |
| Haiku 4.5 | $0.00005 | $0.00051 |
Grade A, and why
product-demo 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 4d 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.
What it actually says
Product Demo
REQUIRED BACKGROUND: marketing-studio skill; also read
${CLAUDE_SKILL_DIR}/../../docs/playbook/capture.md and
${CLAUDE_SKILL_DIR}/../../docs/playbook/remotion.md. Work in ${CLAUDE_SKILL_DIR}/../...
Produces <product>/marketing/assets/<brand>/demo.mp4: real app footage with a
timestamp-driven cursor, subject-safe camera framing, and concise captions.
Recipe
- Toolchain + brand check per marketing-studio. The product's app must be RUNNING (ask the user to start it; never start their stack yourself).
- Capture script:
feeders/capture/record-<brand>-demo.mjs. For a new product copyrecord-noban-demo.mjs: viewport wide enough for the app,deviceScaleFactor: 2, proven ready-locators per view, a step caption per view. Read${CLAUDE_SKILL_DIR}/../../docs/playbook/capture.mdFIRST — especially: camera focus rects are MEASURED from raw footage frames, never derived from click points, and must end before any app-side clipped edge. - Run the capture with
--project <product>; verifycapture OKand the product-owned props/public files it writes. Do not stage product footage in the engine. - Measure/tune focus rects: extract raw frames
(
npx remotion ffmpeg -ss <t> -i <product>/marketing/assets/<brand>/public/<brand>/demo.webm -frames:v 1 f.png), Read them, set focus {x,y,w,h} centers/sizes in the capture script, re-capture (~20s). - Render one proof per view with
--public-dir=<product>/marketing/assets/<brand>/public; check that the product action is legible at delivery size, camera framing is safe, and pointer phases match capture. - Render into the product workspace and deliver per marketing-studio. A full desktop recording is raw material, not automatically an authored edit.
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.
- 4d ago Changed · +2 lines 2d0d8daf4774
- 5d ago Changed · +2 lines 7167b7c3c011
- 11d ago First seen · 31 lines · 50 tokens per session scan A 9c833f2836cb
product-demo is a skill published in the GitHub repository ucsandman/marketing-studio (237 stars, last pushed 5d ago), licensed MIT. It adds 50 tokens to every session and 510 once invoked, about $0.0003 per session on Opus 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.
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