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cold-outbound-optimizer冷出站优化器

Agent Skill

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。

总安装

1,364

周安装

58

GitHub Stars

2,221

下载量

478
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

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

简介

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。

SKILL.md

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

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

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

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 warning/failed 结果,不能写成本站确认安全。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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