Loading...
Loading...
Found 11 Skills
Code review automation for TypeScript, JavaScript, Python, Go, Swift, Kotlin. Analyzes PRs for complexity and risk, checks code quality for SOLID violations and code smells, generates review reports. Use when reviewing pull requests, analyzing code quality, identifying issues, generating review checklists.
Provides structured code review with prioritized feedback. Use when reviewing PRs, analyzing code quality, checking for bugs, or auditing changes. Triggers on "review this", "check this code", PR reviews, or code quality questions.
Perform code review on staged changes or a pull request. Checks for bugs, security issues, performance problems, and best practices. Use when user says "review code", "check my code", "review PR", or "is this code okay".
Performs security-focused differential review of code changes (PRs, commits, diffs). Adapts analysis depth to codebase size, uses git history for context, calculates blast radius, checks test coverage, and generates comprehensive markdown reports. Automatically detects and prevents security regressions.
Coordinate PR mining to extract tribal knowledge and coding standards from GitHub PR history. Use when mining review comments, extracting coding rules, tracking mining jobs, or analyzing reviewer patterns across repositories. Use for "mine PRs", "extract standards", "coding rules from reviews", or "reviewer patterns". Do NOT use for code review, linting, static analysis, or writing new coding standards from scratch without PR data.
Vercel Agent guidance — AI-powered code review, incident investigation, and SDK installation. Automates PR analysis and anomaly debugging. Use when configuring or understanding Vercel's AI development tools.
Generate a visual diff review page (ArchitectureGrid for impacted modules + CodeDiff for hunks + Callouts for risks) from a git range, PR URL, or pasted diff. Use whenever the user asks for a PR review, diff summary, change impact analysis, or pastes `git diff` output. Requires the `hyperscribe` skill (renderer engine).
Meta-skill for analyzing PRs, issues, and user interactions to improve Cursor rules and skills automatically
Conduct rigorous, adversarial code reviews with zero tolerance for mediocrity. Use when users ask to "critically review" my code or a PR, "critique my code", "find issues in my code", or "what's wrong with this code". Identifies security holes, lazy patterns, edge case failures, and bad practices across Python, R, JavaScript/TypeScript, SQL, and front-end code. Scrutinizes error handling, type safety, performance, accessibility, and code quality. Provides structured feedback with severity tiers (Blocking, Required, Suggestions) and specific, actionable recommendations.
Git-based engineering retrospective analyzing commits, PRs, and velocity over configurable windows with monorepo path scoping. Triggers on: "retrospective", "sprint retro", "weekly review", "what did we ship", "engineering retro", "dev summary", "commit analysis".
Reads a PR or branch diff and produces a structured YAML change brief for downstream analytics instrumentation skills. Use this as the first step whenever a user shares a PR link, branch comparison, or raw diff and wants to understand what changed, what needs tracking, or how to instrument a feature. Trigger on phrases like "review this PR", "what changed in this branch", "help me instrument this diff", "check analytics coverage for this change", or any request to start the analytics review workflow.