Summary
If you're doing cold outreach at any volume, you know the pain of researching personalized first lines. This skill takes a prospect list and generates unique openers based on LinkedIn activity, company news, funding rounds, mutual connections, and other signals. It organizes everything by personalization type (congratulations, observations, shared interests) and gives you multiple first line options plus full email templates for each prospect. The format is detailed, maybe more than you need, but you can always strip it down. Claims to save 10+ hours per campaign, which tracks if you're manually researching 100+ prospects. Worth trying if you're tired of "I was on your website" personalization that fools nobody.
Install to Claude Code
npx -y skills add onewave-ai/claude-skills --skill personalization-at-scale --agent claude-codeInstalls into .claude/skills of the current project.
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Files
SKILL.mdView on GitHub
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 standardsreferences/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 anglereferences/output-template.md- full campaign deliverable structurereferences/benchmarks.md- expected lift, A/B reference data, pro tips (do/don't)references/example-campaigns.md- worked campaign examples by persona
Workflow
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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.
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Confirm preferences: which personalization styles to prioritize (1-3), tone (professional, casual, direct, consultative), and any exclusions (recency cutoff, personal topics, sensitive subjects).
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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 fromreferences/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.
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Export in the requested format: CSV with personalization columns, merge fields for the outreach tool (Outreach, Salesloft), individual drafts, or copy-paste blocks.
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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.
Featured
Plug Mailtrap into your AI workflow and let it handle the email.
Connect Mailtrap MCP →Agent, run crypto. Access onchain data & trade routes via 1inch.
Install now →Make coding agent sessions - Searchable, Shareable, Vendor-neutral & Scored.
Try For Free →Your agent targets a perfect 10 Code Health score. Deterministic. Every commit.
Try For Free →Integrate web data into your AI product. One API to scrape website & brand data.
Get API Key Now →belt cli automatically finds the best tools and skills for your agent. image, video, music, tts...
one prompt install →
