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/seo-opsWrote 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/seo-ops)<a href="https://agentmods.dev/skills/ericosiu/ai-marketing-skills/seo-ops"><img src="https://agentmods.dev/badge/skills/ericosiu/ai-marketing-skills/seo-ops/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/seo-ops"><img src="https://agentmods.dev/badge/skills/ericosiu/ai-marketing-skills/seo-ops.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 | $0.01419 |
| Opus 5 | $0.00000 | $0.00709 |
| Sonnet 5 | $0.00000 | $0.00284 |
| Haiku 4.5 | $0.00000 | $0.00142 |
Grade A, and why
seo-ops 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 — 177 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AI SEO Ops
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.
AI-powered SEO operations: keyword intelligence, competitor gap analysis, GSC optimization, and trend detection.
When to Use
- User asks for keyword research, content brief, or SEO analysis
- User wants to find quick-win keywords from Google Search Console
- User needs a competitor gap analysis
- User wants to identify trending topics for content creation
- User asks about decaying content or traffic drops
- User wants a prioritized list of keywords to target
Tools
Content Attack Brief (content_attack_brief.py)
Full keyword intelligence pipeline. Requires AHREFS_TOKEN and GSC auth.
# Run the full brief
python content_attack_brief.py
What it produces:
- Topic fingerprint from your content library
- BOFU money keywords ranked by Impact × Confidence
- Trending keywords with sparkline visualizations
- Competitor gap analysis (keywords they rank for, you don't)
- Decaying page alerts (traffic drops >30%)
- Execution pipeline (auto-create → semi-auto → team)
Output: Prints formatted report to stdout + saves JSON to OUTPUT_DIR/content-attack-brief-latest.json
GSC Client (gsc_client.py)
Google Search Console API client. Works as CLI or importable library.
# CLI usage
python gsc_client.py --queries 50 --days 28
python gsc_client.py --striking # Striking distance keywords (pos 4-20)
python gsc_client.py --pages 100 --days 7
python gsc_client.py --trend # Daily click/impression trend
python gsc_client.py --devices # Mobile vs desktop split
python gsc_client.py --sites # List verified properties
python gsc_client.py --json --queries 25 # JSON output
What ships with it
7 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 · 177 lines · 0 tokens per session scan A 2ce171cf5e83
seo-ops 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 1,419 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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