Takes your best customers and finds 100+ companies that match the same profile using firmographic data, tech stack, growth signals, and a weighted similarity scoring model. The output is genuinely useful: you get ranked prospects with specific contact intelligence, recommended outreach approaches, and a three-tier targeting strategy. The scoring breakdown (industry match 25%, company size 20%, tech stack 15%) is transparent about what drives the recommendations. Good for building target account lists when you're expanding into new markets or need to replicate successful customer patterns. The tier system with expected response rates helps you prioritize outreach realistically instead of treating all lookalikes equally.
npx -y skills add onewave-ai/claude-skills --skill lookalike-customer-finder --agent claude-codeInstalls into .claude/skills of the current project.
Analyze a company's best customers and find similar companies that match the same profile, producing a high-quality, ranked target account list.
references/scoring-model.md - Profile dimensions, weighted scoring model, and score bands.references/output-template.md - Full Markdown report structure (ICP, ranked lookalikes, market insights, targeting strategy, action plan).references/data-sources.md - Recommended enrichment tools and data points to gather.references/examples.md - Best practices, trigger phrases, and an example request.references/scoring-model.md for the five profile dimensions.references/data-sources.md.references/scoring-model.md.references/output-template.md, including market insights, a tiered targeting strategy, and a quick-start action plan.references/examples.md throughout: favor quality over quantity, weight growth signals, and enrich contacts before recommending outreach.juliusbrussee/caveman
mattpocock/skills
shadcn/improve
obra/superpowers
forrestchang/andrej-karpathy-skills
vercel-labs/skills