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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.
Passed 20 of 22 test cases with the skill, and 13 of 22 without it.
and 5 more in the full report
7 fixed13 passed either way2 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 7 test cases the skill fixed. Same model, same prompt, with and without the skill.
When confirming personalization style preferences with a user, how many top styles should be prioritized?
| Checked | Without skill | With skill |
|---|---|---|
| Specifies selecting between 1 and 3 styles | Missed | Passed |
The instructions your model reads when the skill loads.
Generate hundreds of unique, researched first lines in minutes instead of hours, making cold outreach feel warm.
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 personaIngest 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.
test cases passed, vs 13 / 22 without
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