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Agent Skill · 研究检索

cold-outbound-optimizer(冷出站优化器)

cold-outbound-optimizer 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

cold-outbound-optimizer 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为接触敏感数据;许可证信息还不明确,第三方扫描有未通过项,按安装量在研究检索类的 73,675 个 Skill 里排第 39,790。

总安装 1,364周安装 58GitHub Stars 2,221下载 478核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:cold-outbound-optimizer(冷出站优化器)
来源仓库:https://github.com/ericosiu/ai-marketing-skills
仓库路径:skills/cold-outbound-optimizer
安装命令:
npx skills add https://github.com/ericosiu/ai-marketing-skills --skill cold-outbound-optimizer
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/ericosiu/ai-marketing-skills --skill cold-outbound-optimizer

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

cold-outbound-optimizer 审计与优化现有 Instantly 外展活动表现。支持从零开始搭建新 campaign 或导入已有数据进行诊断改进。提供回复率、打开率、预约转化等核心指标的分析建议。首次运行需确认账户权限与数据导出设置,隐私日志本地存储。

适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。

来源仓库内路径:skills/cold-outbound-optimizer

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/ericosiu/ai-marketing-skills --skill cold-outb…;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要接触敏感数据,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

cold-outbound-optimizer 怎么安装?

在终端执行 npx skills add https://github.com/ericosiu/ai-marketing-skills --skill cold-outbound-optim…。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

cold-outbound-optimizer 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

cold-outbound-optimizer 需要什么权限?

权限级别是接触敏感数据。该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

cold-outbound-optimizer 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

cold-outbound-optimizer 用的人多吗?

公开数据是累计安装 1,364 次,近一周安装 58 次,下载 478 次,GitHub 2,221 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

cold-outbound-optimizer 安全吗?

第三方扫描有未通过项,风险较高。除非你确认过源码,否则不建议直接安装到常用环境。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 来源仓库有 2,221 星,维护活跃度相对可查。

先想清楚的地方

  • 需要接触敏感数据,装到常用环境前要先评估影响面。
  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 环境里有大量密钥、凭证,不方便给第三方 Skill 读取的人。
  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
cold-outbound-optimizer

冷出站优化器 · 本页

1,3642,221接触敏感数据未明确未通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

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. See telemetry/README.md.

Cold Outbound Optimizer


Startup: Determine Mode

Ask the user:

  1. Do you have an existing Instantly account with campaigns to audit, or are you starting from scratch?
  2. 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)

1E — Expert Panel Config

Default: 10 experts (see references/expert-panel.md). Ask: "Any industry-specific experts to add, or panelists to swap?" Confirm roster before scoring.


Phase 2: Expert Panel Recursive Scoring

Target: 90/100. Non-negotiable. Iterate until reached.

Round Structure

Each round produces:

  1. Score table — all 10 panelists, individual score (0-100), one-line rationale
  2. Aggregate score — average of all 10
  3. Top weaknesses — ranked list of what's holding the copy back
  4. Changes made — specific edits addressing each weakness
  5. Updated copy — full revised sequence after changes

Scoring Criteria (per panelist's lens — see references/expert-panel.md)

  • Subject line curiosity / open rate potential
  • First sentence pattern interrupt
  • Body clarity and brevity
  • CTA softness and specificity
  • Sequence flow and follow-up logic
  • Deliverability risk signals (spam words, link density)
  • Personalization believability

Rules

  • Scores must be brutally honest. No padding to 90 without earning it.
  • If round score < 90: identify top 3 weaknesses, revise copy, run next round.
  • If round score ≥ 90: finalize copy and proceed to deliverables.
  • Show every round in the final doc — the iteration trail is part of the value.

Phase 3: Deliverables

Strategy Doc

Create a document (Google Doc, Notion, or markdown) with:

  1. Pre-Analysis / Brutal Truth — what the existing campaigns are doing wrong (or baseline if starting from scratch)
  2. ICP Summary — confirmed targeting parameters
  3. Infrastructure Status — account inventory, warmup readiness, capacity math
  4. Scoring Rounds — full panel vote tables for every round
  5. Final Email Copy — all steps for all campaigns, Instantly-ready format
  6. Implementation Plan — step-by-step setup instructions
  7. Capacity Math — accounts × daily send rate = pipeline projections
  8. Weekly Metrics Targets — open rate, reply rate, positive reply rate, meetings booked
  9. STOP List — what to kill immediately
  10. START List — what to launch first

Format Rules for Final Copy

Follow all rules in references/instantly-rules.md and references/copy-rules.md.

Human Review Gate

Do NOT push anything to Instantly automatically. The doc is for human review. Get explicit approval before any API writes.

Iteration

After review, collect feedback and re-run scoring on revised copy if needed.


Capacity Math Formula

Accounts ready (score ≥80, ≥14 days warmup) × 30 emails/day = conservative daily volume
Accounts ready × 50 emails/day = aggressive daily volume
Daily volume × 22 working days = monthly send capacity
Monthly sends × expected reply rate = expected replies
Expected replies × qualification rate = pipeline opportunities

Weekly Metrics Targets (Baselines)

MetricGoodGreat
Open rate40%+60%+
Reply rate3%+7%+
Positive reply rate1%+3%+
Meeting rate0.5%+1.5%+

Adjust targets based on niche and offer. Cold traffic to a free audit converts differently than a paid trial.


Add-On Recommendations (mention but don't build)

  • LinkedIn automation: HeyReach or similar for multi-channel sequences. Separate workflow.
  • Lead enrichment: Clay or Apollo for personalization data before upload.
  • Lead pipeline: Use scripts/lead-pipeline.py for Apollo → LeadMagic → Instantly automation.

Reference Files

FilePurpose
references/instantly-rules.mdVariable syntax, sequence structure, deliverability rules
references/expert-panel.mdDefault 10-expert roster with scoring lenses
references/copy-rules.mdEmail copy rules (first sentence, CTA, stats framing)
references/icp-template.mdICP data collection template
scripts/instantly-audit.pyPulls campaigns, accounts, warmup scores via Instantly v2 API
scripts/lead-pipeline.pyEnd-to-end lead sourcing pipeline
scripts/competitive-monitor.pyCompetitor tracking and intelligence
scripts/cross-signal-detector.pyMulti-source signal detection
scripts/cold-outbound-sender.pySend approved outbound emails

平台分布

Codex

37.15%
按下载量换算178

Claude

26.74%
按下载量换算128

Cursor

20.53%
按下载量换算98

Gemini CLI

9.11%
按下载量换算44

安全审计

Gen Agent Trust Hub

可疑

Socket

通过

Snyk

未通过

权限和风险

接触敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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