Agent-Skills.md

Agent Skills: 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.

UncategorizedID: onewave-ai/claude-skills/personalization-at-scale

Repository

onewave-ai/claude-skills
OneWave-AILicense: MIT
748

Install this agent skill to your local

pnpm dlx add-skill https://github.com/OneWave-AI/claude-skills/tree/HEAD/personalization-at-scale

Skill Files

Browse the full folder contents for personalization-at-scale.

Download Skill

Loading file tree…

personalization-at-scale/SKILL.md

Skill Metadata

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.

Personalization at Scale Skill | Agent Skills