Marketing Skills is a collection of skills for AI coding agents that assist with conversion optimization, copywriting, SEO, analytics, and growth engineering. Technical marketers and founders use it to apply agents to marketing work in tools such as Claude Code, OpenAI Codex, Cursor, and Windsurf. The catalogue entries are the project's own marketing skills and instructions.
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 coreyhaines31/marketingskills --skill product-marketinggit clone --depth 1 https://github.com/coreyhaines31/marketingskillsWrote 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/coreyhaines31/marketingskills/product-marketing)<a href="https://agentmods.dev/skills/coreyhaines31/marketingskills/product-marketing"><img src="https://agentmods.dev/badge/skills/coreyhaines31/marketingskills/product-marketing/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/coreyhaines31/marketingskills/product-marketing"><img src="https://agentmods.dev/badge/skills/coreyhaines31/marketingskills/product-marketing.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk pass
- 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 | $0.00110 | $0.02203 |
| Opus 5 | $0.00055 | $0.01102 |
| Sonnet 5 | $0.00022 | $0.00441 |
| Haiku 4.5 | $0.00011 | $0.00220 |
Grade A, and why
product-marketing 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.
Copies of this mod
3 near-identical copies found in the catalogue:
- product-marketing — 100% identical, 0 lines differ
- product-marketing — 100% identical, 0 lines differ
- product-marketing — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 256 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Product Marketing Context
You help users create and maintain a product marketing context document. This captures foundational positioning and messaging information that other marketing skills reference, so users don't repeat themselves.
The document is stored at .agents/product-marketing.md.
Workflow
Step 1: Check for Existing Context
First, check if .agents/product-marketing.md already exists. Also check .claude/product-marketing.md and the legacy filename product-marketing-context.md (in either .agents/ or .claude/) for older setups — if found anywhere other than .agents/product-marketing.md, offer to move it to the canonical location.
If it exists:
- Read it and summarize what's captured — note its current Document version and the last few Changelog entries so the user sees where the doc stands and what's changed recently
- Ask which sections they want to update
- Only gather info for those sections
- On any substantive save, bump the version and add a changelog entry (see Step 4). This doc is the shared context every other marketing skill reads, so a dated paper trail of what changed and why is worth keeping.
If it doesn't exist, offer two options:
-
Auto-draft from codebase (recommended): You'll study the repo—README, landing pages, marketing copy, package.json, etc.—and draft a V1 of the context document. The user then reviews, corrects, and fills gaps. This is faster than starting from scratch.
-
Start from scratch: Walk through each section conversationally, gathering info one section at a time.
Most users prefer option 1. After presenting the draft, ask: "What needs correcting? What's missing?"
Step 2: Gather Information
If auto-drafting:
- Read the codebase: README, landing pages, marketing copy, about pages, meta descriptions, package.json, any existing docs
- Draft all sections based on what you find
- Present the draft and ask what needs correcting or is missing
- Iterate until the user is satisfied
What ships with it
1 file 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 · 256 lines · 110 tokens per session scan A 6dfd6bd485f6
product-marketing is a skill published in the GitHub repository coreyhaines31/marketingskills (49,629 stars, last pushed 7d ago), licensed MIT. It adds 110 tokens to every session and 2,203 once invoked, about $0.0006 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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