mcpbeat

Personalization At Scale

onewave-ai/personalization-at-scale

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.

4k tokens
context cost
the whole folder, loaded on every use
7
files
instructions only
0
copies elsewhere
how many repositories repackaged it
235
stars on the repo
on the repository, not the skill itself

Install

one command, takes just this skill from the repository
npx skills add https://github.com/OneWave-AI/claude-skills --skill personalization-at-scale

The instruction itself

3 sections, as written by the author

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

  • 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.
  • Confirm preferences: which personalization styles to prioritize (1-3), tone (professional, casual, direct, consultative), and any exclusions (recency cutoff, personal topics, sensitive subjects).
  • Research each prospect across the sources in references/research-sources.md. Identify the strongest, most recent, verifiable angle per prospect.
  • 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.
  • 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.
  • Quality-check the first 10 manually. Confirm each line is specific, recent, relevant, natural, and verifiable before scaling the batch.
  • Export in the requested format: CSV with personalization columns, merge fields for the outreach tool (Outreach, Salesloft), individual drafts, or copy-paste blocks.
  • 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.

How to use it

Copy the folder

Take onewave-ai/personalization-at-scale from the repository into ~/.claude/skills for personal use, or into .claude/skills inside a project.

Check the name does not clash

The agent identifies a skill by the name field in its header. Two skills with the same name cannot sit side by side — one of them will be ignored.