Rechercher

PythonReactSEOPDF
OpenClaw

outreach-sequencer

Create and manage multi-step outreach sequences — LinkedIn messages, cold emails, and follow-ups with personalization. Use when asked to "send outreach", "create email sequence", "follow up with leads", "start a drip campaign", "send LinkedIn messages", "personalized outreach", or any automated multi-step communication workflow.

aspenas0 installations selon la source☆ 0 Étoiles du dépôt

Installation

Suivez les instructions du dépôt pour votre agent. Consultez les fichiers et dépendances avant l’installation.

SkillHub CLI

skillhub install aspenas/ironclaw-outreach-sequencer

Examinez la source et la compatibilité, puis suivez les étapes d’installation.

Donnez le lien à votre agent et demandez-lui d’examiner instructions et dépendances avant d’expliquer les étapes.

Voir la source ↗Guides

Instructions

Outreach Sequencer — Multi-Step Personalized Campaigns

Design, schedule, and execute multi-step outreach sequences across LinkedIn and email. Each message is personalized per lead using their profile data from DuckDB.

Sequence Templates

Template 1: LinkedIn Connection + Message
Day 0: Send LinkedIn connection request (with note)
Day 1: If accepted → Send intro message
Day 3: If no reply → Follow-up message
Day 7: If no reply → Break-up / value-add message
Template 2: Cold Email Sequence
Day 0: Initial cold email
Day 3: Follow-up (reply to original thread)
Day 7: Value-add email (case study, resource)
Day 14: Break-up email ("closing the loop")
Template 3: Multi-Channel
Day 0: LinkedIn connection request
Day 2: Cold email (if not connected on LinkedIn)
Day 4: LinkedIn message (if connected) OR email follow-up
Day 7: Final touch (whichever channel they engaged on)

Personalization Engine

Each message is generated per-lead using their DuckDB profile data. Use these variables:

Variable Source Example
{first_name} Name field (split) "Jane"
{company} Company field "Acme Corp"
{title} Title field "CTO"
{mutual} Shared connections/background "Stanford"
{trigger} Why reaching out now "saw your Series A"
{value_prop} What you offer them "AI-powered analytics"
{pain_point} Their likely challenge "scaling engineering team"
Personalization Rules
  • Never use generic openers like "I hope this finds you well"
  • Reference something specific: recent post, company news, shared background
  • Keep LinkedIn messages under 300 chars (connection note limit)
  • Keep cold emails under 150 words (respect attention)
  • Vary language across leads — don't send identical messages to people at the same company
  • Match tone to seniority: C-suite gets concise/strategic, ICs get technical/peer-level
Message Gene...

Informations sur la source

Source
github
Repository
openclaw/skills
Path
skills/aspenas/ironclaw-outreach-sequencer
Version
—
Commit
4542f463acc7af1fcd674a1643ae4b3c2a8312e9
Source de classification
rules
Statut
active
Visibilité
public

Ces informations proviennent de l’analyse indexée et peuvent être anciennes. Vérifiez les fichiers actuels.

Contenu extrait

SKILL.md
# Outreach Sequencer — Multi-Step Personalized Campaigns

Design, schedule, and execute multi-step outreach sequences across LinkedIn and email. Each message is personalized per lead using their profile data from DuckDB.

## Sequence Templates

### Template 1: LinkedIn Connection + Message
```
Day 0: Send LinkedIn connection request (with note)
Day 1: If accepted → Send intro message
Day 3: If no reply → Follow-up message
Day 7: If no reply → Break-up / value-add message
```

### Template 2: Cold Email Sequence
```
Day 0: Initial cold email
Day 3: Follow-up (reply to original thread)
Day 7: Value-add email (case study, resource)
Day 14: Break-up email ("closing the loop")
```

### Template 3: Multi-Channel
```
Day 0: LinkedIn connection request
Day 2: Cold email (if not connected on LinkedIn)
Day 4: LinkedIn message (if connected) OR email follow-up
Day 7: Final touch (whichever channel they engaged on)
```

## Personalization Engine

Each message is generated per-lead using their DuckDB profile data. Use these variables:

| Variable | Source | Example |
|----------|--------|---------|
| `{first_name}` | Name field (split) | "Jane" |
| `{company}` | Company field | "Acme Corp" |
| `{title}` | Title field | "CTO" |
| `{mutual}` | Shared connections/background | "Stanford" |
| `{trigger}` | Why reaching out now | "saw your Series A" |
| `{value_prop}` | What you offer them | "AI-powered analytics" |
| `{pain_point}` | Their likely challenge | "scaling engineering team" |

### Personalization Rules
- **Never use generic openers** like "I hope this finds you well"
- **Reference something specific**: recent post, company news, shared background
- **Keep LinkedIn messages under 300 chars** (connection note limit)
- **Keep cold emails under 150 words** (respect attention)
- **Vary language across leads** — don't send identical messages to people at the same company
- **Match tone to seniority**: C-suite gets concise/strategic, ICs get technical/peer-level

### Message Gene...

Skills associés

OpenClaw

sixtyfour-skill

rxhxm

Agent Skill (SKILL.md) for Sixtyfour AI — People & company intelligence API. Enrich leads, find emails/phones, qualify prospects, search people. For Claude Code, Codex, OpenClaw, Cursor.

OpenClaw

139mail

chang-tong

139邮箱邮件收发 Skill - 支持 IMAP/SMTP 协议,兼容139/QQ/163/Gmail等主流邮箱 功能: 1. 发送邮件(SMTP) 2. 接收邮件(IMAP) 3. 查看收件箱列表 4. 查看未读邮件 当用户提到 "发邮件"、"收邮件"、"查看邮件"、"邮箱"...

OpenClaw

ABM Outbound

dru-ca

Multi-channel ABM automation that turns LinkedIn URLs into coordinated outbound campaigns. Scrapes profiles, enriches with Apollo (email + phone), gets mailing addresses via Skip Trace, then orchestrates email...