Agent skill · marketing growth · 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.
Why this skill is useful
Provides a structured workflow and templates for generating personalized outreach at scale, which the AI wouldn't reliably create on its own.
What it needs
About 1k tokens when loaded. Last updated 2026-07-15. 242 stars on the source repository.
What this skill does
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. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills onewave-ai/personalization-at-scale