Explorar skills

Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes

Visual Regression Testing — screenshot comparison before and after changes. Use when user wants to check for visual regressions, compare UI changes, or verify CSS/layout changes didn't break anything.

Top 1% SEO strategist — ruthlessly analyzes GSC, Bing, and GA4 data to dominate search rankings, win AI citations, and build lead funnels. Every recommendation backed by data.

Use when about to claim work is complete, fixed, or passing, before committing or creating PRs - requires running verification commands and confirming output before making any success claims; evidence before assertions always

Sprint retrospective — analyzes git velocity, commit patterns, test health, and shipping cadence. Use after a sprint, at the end of the week, or when the user wants to reflect on progress.

Use when starting feature work that needs isolation from current workspace or before executing implementation plans - creates isolated git worktrees with smart directory selection and safety verification

AI Build Cost Tracker — track how much AI is costing you per feature. Use when user wants to track AI spending, understand cost per feature, optimize AI usage, or budget their Claude/GPT costs.

Living Architecture Map — auto-generate Mermaid diagrams of your codebase. Use when user wants to visualize architecture, understand code structure, generate diagrams, or document system design.

Use when you have a written implementation plan to execute in a separate session with review checkpoints

Manage project learnings across sessions. Save, search, recall, digest, prune, and export learnings that compound over time. Use when user wants to record, recall, or share project knowledge.

Instant Project Onboarding — generate a complete onboarding guide for any project. Use when user wants to onboard a new developer, understand a new codebase, or generate project documentation.

Use when receiving code review feedback, before implementing suggestions, especially if feedback seems unclear or technically questionable - requires technical rigor and verification, not performative agreement or blind implementation