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personalization-at-scale — Claude Code skill: first lines at volume

This skill writes personalized first lines for hundreds of prospects from company news, LinkedIn activity and mutual connections. Useful when cold outreach goes out in batches.

Install into Claude Code · Skills CLI (Vercel) All methods and platforms ↓
npx skills add OneWave-AI/claude-skills --skill personalization-at-scale -a claude-code
Open on GitHub

What personalization-at-scale does

Feed it a prospect list as CSV or pasted text. First name, last name, title and company are required; LinkedIn URL, email, website, industry, size and location get used when present. For each person the skill looks for the strongest recent angle: company news, a LinkedIn post, a mutual connection, hiring, tech stack, thought leadership.

The references/ folder holds the working material: signal sources and personalization styles, first-line patterns by angle, fallback lines for prospects with no angle, the campaign output structure, benchmark notes and worked examples by persona. Each prospect gets 2–3 first-line options with a High/Medium/Low confidence score and notes on alternative angles.

Quality-check the first 10 lines by hand before scaling the batch. That step matters because it shows where the skill picked a stale angle. Export comes as CSV with personalization columns, merge fields for Outreach or Salesloft, individual drafts, or copy-paste blocks. The skill advises refreshing personalizations every 30 days, since people's activity moves on.

What it helps with

  • draft first lines for hundreds of prospects in one pass
  • find an angle from company news and LinkedIn posts
  • drop personalization into Outreach or Salesloft merge fields
  • write a fallback line for a prospect with no obvious angle
  • refresh stale personalizations before the next send

Example prompts for the agent

  • Here's my prospect list as CSV — write personalized first lines from company news
  • Give me 2 first-line options per prospect with confidence scores
  • Export the result as a CSV with columns for Salesloft

How to install personalization-at-scale

1Skills CLI (Vercel)

npx skills add OneWave-AI/claude-skills --skill personalization-at-scale -a claude-code

2Manually: put the files in place

~/.claude/skills/personalization-at-scale/SKILL.md

Copy the whole skill folder; for one project use .claude/skills/personalization-at-scale/

Step by step, with commands for each platform: How to install skills in Claude Code: five ways

Questions about personalization-at-scale

How do I install personalization-at-scale in Claude?

Run npx skills add OneWave-AI/claude-skills --skill personalization-at-scale -a claude-code. The skill then sits at ~/.claude/skills/personalization-at-scale/SKILL.md.

What does personalization-at-scale do?

It generates personalized first lines for hundreds of prospects using company news, LinkedIn activity and mutual connections. Output includes confidence scores and an export shaped for your outreach tool.

What do I need before running it?

A prospect list with first name, last name, title and company, as CSV or pasted text. Fields like LinkedIn URL, industry and location are used when they're filled in.

Source text

SKILL.md · MIT
---
name: personalization-at-scale
description: Generate unique personalized first lines for hundreds of prospects using company news, LinkedIn activity, and mutual connections. Saves 10+ hours of manual research per campaign. Use when you need personalized outreach at volume.
---

# Personalization at Scale

Generate hundreds of unique, researched first lines in minutes instead of hours, making cold outreach feel warm.

## Contents

- `references/research-sources.md` - signal sources, personalization styles, quality standards
- `references/patterns-by-type.md` - sample first lines and tables for each angle (congrats, observation, mutual connection, company news, hiring, tech stack, thought leadership, shared background)
- `references/fallbacks.md` - role/stage/industry/competitor lines for prospects with no angle
- `references/output-template.md` - full campaign deliverable structure
- `references/benchmarks.md` - expected lift, A/B reference data, pro tips (do/don't)
- `references/example-campaigns.md` - worked campaign examples by persona

## Workflow

1. Ingest the prospect list (CSV or pasted). Require First Name, Last Name, Title, Company; use LinkedIn URL, email, website, industry, size, and location when available.

2. Confirm preferences: which personalization styles to prioritize (1-3), tone (professional, casual, direct, consultative), and any exclusions (recency cutoff, personal topics, sensitive subjects).

3. Research each prospect across the sources in `references/research-sources.md`. Identify the strongest, most recent, verifiable angle per prospect.

4. Match each prospect to its angle and draft from the matching pattern in `references/patterns-by-type.md`. For prospects with no angle, draft from `references/fallbacks.md`.

5. Generate 2-3 first-line options per prospect, each with a confidence score (High/Medium/Low) and notes on alternative angles. Follow the structure in `references/output-template.md`.

6. Quality-check the first 10 manually. Confirm each line is specific, recent, relevant, natural, and verifiable before scaling the batch.

7. Export in the requested format: CSV with personalization columns, merge fields for the outreach tool (Outreach, Salesloft), individual drafts, or copy-paste blocks.

8. Track response rates by personalization type and refresh personalizations every 30 days as activity changes.

See `references/benchmarks.md` for target success rates and `references/example-campaigns.md` for persona-specific approaches.

© OneWave-AI · MIT · OneWave-AI/claude-skills

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