AI Marketing Skills is a collection of open-source workflows that help AI coding agents handle marketing and sales work, including growth experiments, pipeline management, content operations, outbound outreach, SEO, and finance analysis. It is intended for marketing and sales teams that want reusable agent-driven processes. The catalogue entries package these workflows as skills for compatible coding agents.
Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/ericosiu/ai-marketing-skillsnpx agentmods add skills/ericosiu/ai-marketing-skills/net-new-video-editorWrote 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/ericosiu/ai-marketing-skills/net-new-video-editor)<a href="https://agentmods.dev/skills/ericosiu/ai-marketing-skills/net-new-video-editor"><img src="https://agentmods.dev/badge/skills/ericosiu/ai-marketing-skills/net-new-video-editor/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/ericosiu/ai-marketing-skills/net-new-video-editor"><img src="https://agentmods.dev/badge/skills/ericosiu/ai-marketing-skills/net-new-video-editor.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00096 | $0.00919 |
| Opus 5 | $0.00048 | $0.00460 |
| Sonnet 5 | $0.00019 | $0.00184 |
| Haiku 4.5 | $0.00010 | $0.00092 |
Grade A, and why
net-new-video-editor 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 13d 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 — 99 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Net-New Video Editor
Create a reversible first edit from fresh recordings. Keep creative decisions in JSON and pixel operations in the bundled renderer.
Preamble
Run from the repository root when the optional shared telemetry helpers are present:
python3 telemetry/version_check.py 2>/dev/null || true
python3 telemetry/telemetry_init.py 2>/dev/null || true
Remote telemetry is opt-in and never includes content, file paths, repository names, or credentials.
Establish the package
Read references/project-contract.md. Locate the exact source recordings, transcript, idea card or brief, proof assets, and screen recordings. Never substitute another recording, brand, account, or asset library.
Initialize a new project only when the destination is clear:
python3 scripts/net_new_video_editor.py init --project <project-dir>
Copy or point only user-authorized inputs into the generated package. Preserve originals.
Inspect before editing
Run:
python3 scripts/net_new_video_editor.py inspect --project <project-dir>
Review intake-report.json. Stop when the package has no playable take, the requested target does not match the supplied footage, or required external assets are missing.
Build the edit plan
Use the transcript and brief to create edit-plan-clean.json. Treat the spoken hook and claim boundaries as ground truth.
- Select one source take explicitly.
- Keep segment order intentional and timestamps within the source duration.
- Remove clear false starts, long dead space, and isolated filler only when the cut remains natural.
- Preserve breaths that help meaning.
- Put the hook on screen for at most five seconds.
- Use captions in short readable phrases.
- Add proof or screen inserts only when supplied and relevant. The bundled renderer handles the base assembly; add complex overlays in a separate, documented pass.
- Normalize speech without clipping.
For a second version, copy the plan to edit-plan-aggressive.json and make only named retention edits. Do not silently change factual claims.
What ships with it
4 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.
- 13d ago First seen · 99 lines · 96 tokens per session scan A 87d82d1daae5
net-new-video-editor is a skill published in the GitHub repository ericosiu/ai-marketing-skills (3,521 stars, last pushed 5d ago), licensed MIT. It adds 96 tokens to every session and 919 once invoked, about $0.0005 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
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
local-ai-agents
Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…
insight-error-page
Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…