Loading...
Loading...
Found 142 Skills
Use when "statistical modeling", "A/B testing", "experiment design", "causal inference", "predictive modeling", or asking about "hypothesis testing", "feature engineering", "data analysis", "pandas", "scikit-learn"
Generate, evaluate, and A/B test email subject lines for maximum open rates. Includes formulas for curiosity, urgency, personalization, and more. Trigger phrases: "email subject line", "subject line ideas", "email subject", "write subject lines", "A/B test subject lines", "improve open rates", "email open rate", "subject line formulas".
Vercel Flags guidance — feature flags platform with unified dashboard, Flags Explorer, gradual rollouts, A/B testing, and provider adapters. Use when implementing feature flags, experimentation, or staged rollouts.
Measure, report on, and optimize marketing performance across channels and campaigns. Trigger on requests for performance dashboards, campaign result analysis, channel metrics review (email, social, paid ads, SEO, content), trend analysis, forecasting, attribution modeling, A/B testing guidance, or actionable optimization recommendations.
A/B test agent variants measuring quality and total session token cost across simple and complex benchmarks. Use when creating compact agent versions, validating agent changes, comparing internal vs external agents, or deciding between variants for production. Use for "compare agents", "A/B test", "benchmark agents", or "test agent efficiency". Do NOT use for evaluating single agents, testing skills, or optimizing prompts without variant comparison.
Use this skill when the user requests to "generate cover", "cover copy", "XHS title", "optimize title", says "help me write a cover", or needs Xiaohongshu cover text and title variants. Based on cognitive psychology and behavioral economics, it identifies content types and authoritative elements, automatically selects driving strategies, and outputs three versions of solutions: aggressive, balanced, and conservative. Each version includes cover copy plus 3 titles, accompanied by four-dimensional ratings and A/B testing suggestions. Do NOT trigger this skill for scenarios like writing video scripts (use li-writer) or optimizing openings (use li-opening).
This skill should be used when the user asks to review, proofread, check, or evaluate content. It provides comprehensive text review (grammar, logic, compliance) and version evaluation (A/B testing, comparison analysis). Text review automatically adds AI disclaimer at the end.
When the user wants to A/B test App Store product page elements to improve conversion rate. Also use when the user mentions "A/B test", "product page optimization", "test my screenshots", "test my icon", "conversion rate optimization", "CPP", or "custom product pages". For screenshot design, see screenshot-optimization. For metadata optimization, see metadata-optimization.
Manage outbound sequences in Apollo.io — create, configure, optimize deliverability, and analyze performance. Use when creating an Apollo sequence, fixing Apollo email deliverability, setting up A/B tests in Apollo, configuring Apollo mailboxes, analyzing Apollo sequence stats, or troubleshooting Apollo sending issues. Do NOT use for designing cadence strategy and content (use /sales-cadence), general Apollo platform help (use /sales-apollo), or non-Apollo sequence tools (use /email-sequence).
Analyzes and rewrites prompts for better AI output, creates reusable prompt templates for marketing use cases (ad copy, email campaigns, social media), and structures end-to-end AI content workflows. Use when the user wants to improve prompts for AI-assisted marketing, build prompt templates, or optimize AI content workflows. Also use when the user mentions 'prompt engineering,' 'improve my prompts,' 'AI writing quality,' 'prompt templates,' or 'AI content workflow.'
Master metrics definition, KPI tracking, dashboarding, A/B testing, and data-driven decision making. Use data to guide product decisions.
Evaluate Omni AI query generation accuracy by running test prompts through the Omni CLI, comparing generated query JSON against expected results, and scoring accuracy. Use this skill whenever someone wants to evaluate Omni AI, benchmark Blobby, run regression tests, compare AI output across branches or configurations, test prompt variations, measure AI quality, run A/B tests on model changes, assess impact of context changes, or any variant of "run evals", "test Blobby", "benchmark query generation", "compare AI results", "regression test", "how accurate is the AI", or "measure the impact of my changes".