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 agentmods add skills/genfeedai/skills/outbound-optimizernpx skills add genfeedai/skills --skill outbound-optimizergit clone --depth 1 https://github.com/genfeedai/skillsWrote 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/genfeedai/skills/outbound-optimizer)<a href="https://agentmods.dev/skills/genfeedai/skills/outbound-optimizer"><img src="https://agentmods.dev/badge/skills/genfeedai/skills/outbound-optimizer.svg" alt="Measured on agentmods" height="20"></a>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 | $0.00052 | $0.02920 |
| Opus 5 | $0.00026 | $0.01460 |
| Sonnet 5 | $0.00010 | $0.00584 |
| Haiku 4.5 | $0.00005 | $0.00292 |
Grade A, and why
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 5d 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 — 384 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Outbound Optimizer - Cold Outreach Revenue Machine
Overview
Executes an outreach transformation using Alex Hormozi's outbound principles — diagnosing current messaging and producing high-converting templates that lead with value, prove personalization, and make zero-commitment offers.
Hormozi's Core Principle: "Outbound is the fastest way to revenue. Most people just suck at it. Lead with value, not pitch."
The Framework: Value-First Outbound
Key Principles:
- Lead with Value: Solve their problem before asking for anything
- Prove Research: Show you know THEM, not just their industry
- Zero Commitment First: Offer something with no strings attached
- Natural CTA: Make the next step feel obvious, not pushy
- Volume + Quality: Bad outreach at volume = spam. Good outreach at volume = revenue.
Execution Workflow
Step 1: ICP Clarity
Ask the user:
Who exactly are you reaching out to?
- What's their job title/role?
- What company size/type?
- What industry or vertical?
- What pain are they experiencing RIGHT NOW?
- Why should THEY specifically care about what you offer?
- What would make them say "this person actually gets my situation"?
ICP Framework:
| Element | Question | Example |
|---|---|---|
| Title | Who decides? | Marketing Directors |
| Company | What type? | B2B SaaS, $1-10M ARR |
| Pain | What hurts? | Content isn't converting to leads |
| Trigger | Why NOW? | Just raised funding, hiring marketers |
| Proof | Why YOU? | We helped [similar company] get [result] |
Step 2: Current Message Audit
Ask the user:
Share your current outreach message(s):
- What's your current cold email or DM?
- What's your subject line?
- What's your response rate? (Be honest)
- What responses do you typically get?
- How many do you send per day/week?
Common Problems to Diagnose:
| Issue | Symptom | Fix |
|---|---|---|
| Too long | Wall of text | Under 100 words |
| No hook | Boring first line | Lead with insight |
| No research | Generic message | Personalize first line |
| All about YOU | "I/We/Our" focus | Talk about THEM |
| Pushy CTA | "Book a call" immediately | Zero-commitment offer |
| No value | Just asking for time | Give something first |
What ships with it
2 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.
- 5d ago First seen · 384 lines · 52 tokens per session scan A b59a79238980
outbound-optimizer is a skill published in the GitHub repository genfeedai/skills (2 stars, last pushed 1mo ago), licensed MIT. It adds 52 tokens to every session and 2,920 once invoked, about $0.0003 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 2026-08-31.
Other skills, from other repositories
self-media-content-brief
Skill "self-media-content-brief" from yanhua1010/self-media-content-workflow, covering 创作简报, 原则, 需要确认的信息, 提问路由 and 输出创作简报.
self-media-content-workflow
通用自媒体内容生产与经营工作流。用于自媒体内容创作、选题策划、热点或竞品研究、多平台改写、短视频脚本、数字人视频、发布包、公众号草稿、内容数据分析、周复盘、月复盘和继续未完成任务。负责识别请求类型，调用创作简报、内容策略、热点竞品、平台文案、短视频、数据复盘和交付归档模块，并管理方向确认、标题确认、终稿确认和发布授权。.
self-media-platform-copywriting
将已确认的母题、证据和创作简报写成平台原生内容。用于 X 短帖、长帖或线程，小红书图文，微信公众号文章，视频号或抖音发布文案，以及同一母题的多平台适配。强调各平台独立设计标题、开头、证据顺序、结构和行动，不做机械缩写或共享正文式的一稿多发。.
self-media-short-video
把已确认的母题或文案转成可直接拍摄、录屏或交给视频工具制作的短视频方案，也支持在用户确认肖像与声音权利并完成平台手动上传后制作数字人视频。用于视频号、抖音、小红书视频和其他竖屏短视频的口播稿、前 3 秒钩子、分镜、字幕、录屏清单、封面、话题、BGM 建议、数字人制片包和发布文案。.
self-media-wechat-publisher
把已确认的公众号终稿 Markdown 排版并写入微信公众号草稿箱。用于用户说"发布到公众号、写入草稿箱、公众号排版、换个排版主题、发小绿书图片消息"等场景。自动上传封面与文内图片，支持多主题与自定义 CSS、多账号和 server 模式。只创建草稿不群发，凭据只通过环境变量提供，未安装适配工具时交付手动发布包。.
self-media-content-analytics
分析单篇、系列、周度或月度自媒体数据并形成可执行复盘。用于读取平台后台截图、CSV、表格、公开链接或用户提供的数据，计算关注效率和深度互动，比较同平台基线，归因选题、标题、封面、开头、结构、发布时间、标签和行动，并输出加码、改包装、再适配、停止或继续收集样本的决策。.