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 matteotitta/genesys-skills --skill onboarding-videogit clone --depth 1 https://github.com/matteotitta/genesys-skillsWrote 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/matteotitta/genesys-skills/onboarding-video)<a href="https://agentmods.dev/skills/matteotitta/genesys-skills/onboarding-video"><img src="https://agentmods.dev/badge/skills/matteotitta/genesys-skills/onboarding-video/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/matteotitta/genesys-skills/onboarding-video"><img src="https://agentmods.dev/badge/skills/matteotitta/genesys-skills/onboarding-video.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00155 | $0.03407 |
| Opus 5 | $0.00077 | $0.01703 |
| Sonnet 5 | $0.00031 | $0.00681 |
| Haiku 4.5 | $0.00015 | $0.00341 |
Grade A, and why
onboarding-video 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 12d 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 — 264 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Onboarding Video
Renders a short, punchy onboarding video that demonstrates one product feature in action. Output is brand-bound MP4 via the Hyperframes engine. Length: 3–8 seconds per beat, stitched into a ~15–30 second video. Style: cropped pieces of the UI animating through the interaction that proves the feature works — never the whole screen.
This is the rendered counterpart to /onboarding-video-script. The script skill writes the talk track for a founder to read aloud over a screen-recorded video; this skill renders the video itself, motion-graphics style, from stills. They compose — script the talk track first, then render the visual layer (optional pairing).
Inherits the rendering engine, brand-kit binding, and DESIGN.md token contract from /product-ui-frames (the generic product-UI animation engine). Adds four craft rules on top: UI-pieces doctrine, caption discipline, cursor discipline, stills-intake gate.
The body holds decision-grade context (when to invoke, validation gate, the four rules summarised). Full craft for each rule lives in the premium reference.
Doctrine inherited (Step 7 — 0626 rollout)
Output complies with:
output-tenets.md— the seven tenetsoutput-simplicity.md— length caps, three-layer source placement, robot-tells bandesign-production.md— DESIGN.md contract for visual output- Step 6 calibration: see [[feedback_execution_doctrine_refinements_step6]]
Refinements applied to this skill:
| Code | Refinement | How it lands in onboarding-video |
|---|---|---|
| R1 | Source placement (three layers) | Rendered MP4 is end-customer-facing. No source frames in the video itself. Brand-kit citations + DESIGN.md tokens live in sidecar metadata for QA only. Captions never carry [VERIFIED:...] overlays. |
| R3 | Product-update tone | Captions frame as "[Product] does X" not "we are thrilled to introduce X." Even on launch-day onboarding videos. The visual demonstrates; the caption labels — neither oversells. |
| R6 | CTA hierarchy | End-card CTA names the product-action tied to the feature being demonstrated — "open [Feature] in the dashboard" — NOT sign-up (viewer already signed up to see onboarding). Per Step 6 warm-base = product-action rule. |
| R9 | Action-oriented section names | Caption beats are verb-led ("Connect / See the runway / Open Reporting") — not status-led ("Setup / Dashboard view / Features"). |
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.
- 12d ago First seen · 264 lines · 155 tokens per session scan A 24e85ecf17e2
onboarding-video is a skill published in the GitHub repository matteotitta/genesys-skills (36 stars, last pushed 1mo ago), licensed MIT. It adds 155 tokens to every session and 3,407 once invoked, about $0.0008 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.
Other skills, from other repositories
gingiris-b2b-growth
🇺🇸 B2B SaaS Growth — PLG vs SLG Playbook — Diagnose whether your problem is distribution, pricing, or PMF. PLG/SLG selection by ACV and sales cycle, the 5-stage path from $0 to $10M ARR, NRR discipline, affiliate & channel motion, enterprise tiering. Built from HeyGen, Deel, Vercel, Supabase, Snowflake patterns.…
gr-b2b-growth
A guide to growing a business-to-business software product from early user research to large-scale sales. B2B software is sold to companies rather than individual consumers.
go-to-market-playbook
A reusable Go-to-Market strategy template for both B2B and B2C launches. Covers positioning, messaging, ICP definition, channel selection, and competitive analysis frameworks. By @WeiYipei.
gingiris-go-global
🇺🇸 AI Product / SaaS Go-Global Complete SOP — From competitor research to launch to monetization. A full-cycle playbook covering Phase 0-5 (market validation, positioning, first 100 users, user interviews, beta-to-growth) plus open-source launch, Product Hunt, Reddit, SEO/GEO, conversion, and org principles.…
gr-competitor-research
Your competitor just launched. You have no idea how they grew so fast. Should you reverse-engineer their website? Track their social media? Map their growth flywheel? This gives you the complete SOP — from Wayback Machine snapshots to X/Twitter propagation analysis to growth flywheel scoring. Built from 150+ AI…
ai-launch-playbook
Launch your AI product to global attention — the playbook behind Manus, Devin, and AFFiNE's breakout launches. Covers AI-specific GTM strategy, hype cycle management, waitlist tactics, and multi-market rollout for maximum day-one impact.