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/outbound-engineWrote 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/outbound-engine)<a href="https://agentmods.dev/skills/ericosiu/ai-marketing-skills/outbound-engine"><img src="https://agentmods.dev/badge/skills/ericosiu/ai-marketing-skills/outbound-engine/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/outbound-engine"><img src="https://agentmods.dev/badge/skills/ericosiu/ai-marketing-skills/outbound-engine.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 | $0.00102 | $0.01628 |
| Opus 5 | $0.00051 | $0.00814 |
| Sonnet 5 | $0.00020 | $0.00326 |
| Haiku 4.5 | $0.00010 | $0.00163 |
Grade A, and why
cold-outbound-optimizer 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 — 173 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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.
Cold Outbound Optimizer
Startup: Determine Mode
Ask the user:
- Do you have an existing Instantly account with campaigns to audit, or are you starting from scratch?
- Do you have an Instantly API key? (Required for audit mode.)
If API key provided → run scripts/instantly-audit.py to pull campaigns, account inventory, and warmup scores before proceeding.
Phase 1: Discovery & Audit
1A — Infrastructure Check (if API key available)
Run python3 scripts/instantly-audit.py --api-key <KEY> and report:
- Active campaigns (name, status, reply rate, open rate)
- Sending accounts (count, warmup score, daily limit)
- Domain inventory
- Warmup gaps: any account with score <80 or <14 days warmup → flag as NOT ready
1B — Performance Data
- Pull campaign analytics from Instantly
- Ask: "Do you have a spreadsheet with historical outbound data?" If yes, request link.
1C — ICP Definition
If no ICP defined, collect:
- Titles: Who are you targeting? (e.g., VP Marketing, Head of Growth)
- Industries: Which verticals?
- Company size: Employee count or revenue range?
- Revenue floor: Minimum ARR/revenue to qualify?
- Anti-ICP: Who to explicitly exclude?
Use references/icp-template.md as the collection template.
1D — Business Context
Collect:
- What do you sell? (One sentence, no jargon)
- What's the primary offer? (Free trial, audit, demo, consultation)
- Real URLs to reference (pricing page, case studies, relevant content)
- Any proof points? (Client results, stats, social proof)
What ships with it
12 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.
- .env.example 854 B
- README.md 6.2 KB
- references/copy-rules.md 4.7 KB
- references/expert-panel.md 4.7 KB
- references/icp-template.md 3.2 KB
- references/instantly-rules.md 2.9 KB
- requirements.txt 17 B
- scripts/cold-outbound-sender.py 8.3 KB runs code
- scripts/competitive-monitor.py 17 KB runs code
- scripts/cross-signal-detector.py 11 KB runs code
- scripts/instantly-audit.py 13 KB runs code
- scripts/lead-pipeline.py 21 KB runs code
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 · 173 lines · 102 tokens per session scan A d7e4d381b025
cold-outbound-optimizer is a skill published in the GitHub repository ericosiu/ai-marketing-skills (3,521 stars, last pushed 4d ago), licensed MIT. It adds 102 tokens to every session and 1,628 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.
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