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/short-form-pipelineWrote 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/short-form-pipeline)<a href="https://agentmods.dev/skills/ericosiu/ai-marketing-skills/short-form-pipeline"><img src="https://agentmods.dev/badge/skills/ericosiu/ai-marketing-skills/short-form-pipeline/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/short-form-pipeline"><img src="https://agentmods.dev/badge/skills/ericosiu/ai-marketing-skills/short-form-pipeline.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 | $0.00000 | $0.00994 |
| Opus 5 | $0.00000 | $0.00497 |
| Sonnet 5 | $0.00000 | $0.00199 |
| Haiku 4.5 | $0.00000 | $0.00099 |
Grade A, and why
short-form-pipeline 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 — 103 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Short-Form Video Clip Pipeline — Skill
Preamble (runs on skill start)
# Version check (silent if up to date)
python3 telemetry/version_check.py 2>/dev/null || true
# Telemetry opt-in (first run only, then remembers your choice)
python3 telemetry/telemetry_init.py 2>/dev/null || true
Privacy: This skill logs usage locally to
~/.ai-marketing-skills/analytics/. Remote telemetry is opt-in only. No code, file paths, or repo content is ever collected. Seetelemetry/README.md.
Extract viral short-form clips (TikTok, Reels, Shorts) from long-form YouTube videos. Handles download, transcription, AI segmentation, cutting, vertical cropping, and caption burn-in.
Prerequisites
yt-dlpandffmpeginstalledANTHROPIC_API_KEYenvironment variable set- Python dependencies from
requirements.txtinstalled - Optional:
mediapipeandopencv-pythonfor face-detected smart crop
Quick Start
Single video → clips
python3 scripts/shortform_pipeline.py \
--url "https://www.youtube.com/watch?v=VIDEO_ID" \
--max-clips 3 \
--output-dir ./output
Standalone clipper (no Claude, heuristic scoring)
python3 scripts/video_clipper.py --url "https://www.youtube.com/watch?v=VIDEO_ID"
Pipeline Overview
- Download — yt-dlp fetches video + auto-generated VTT captions
- Transcribe — Whisper generates word-level timestamps (falls back to YouTube captions)
- Segment — Claude identifies 2–5 best 30–60s moments with hook scoring ≥7/10
- Cut Verification — Second Claude pass verifies each clip ends on a complete thought
- Cut — FFmpeg extracts each clip from the source video
- Vertical Crop — Layout-aware 16:9 → 9:16 conversion with face detection
- Caption Burn — TikTok-style word-highlighted captions (ASS format) burned in
Key Files
| File | Purpose |
|---|---|
scripts/shortform_pipeline.py |
Full pipeline: download → segment → cut → crop → caption |
scripts/video_clipper.py |
Standalone clipper with heuristic scoring (no Claude needed) |
scripts/clip_sender.py |
Helper for clip delivery and review workflow |
What ships with it
5 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 · 103 lines · 0 tokens per session scan A a6bbe961a2fd
short-form-pipeline is a skill published in the GitHub repository ericosiu/ai-marketing-skills (3,521 stars, last pushed 4d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 994 tokens. 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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