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Found 920 Skills
Comprehensive codebase review and parallel agent-based remediation skill. Use PROACTIVELY when agent needs to perform full codebase audit, generate master findings report with quantified metrics, and execute remediation using parallel goodvibes background agents (max 6 concurrent, one task per agent with fresh context). Triggers on: codebase review, code audit, full project analysis, quality assessment, technical debt analysis, parallel remediation, bulk fixes.
Behavioral guidelines to reduce common LLM coding mistakes. Use when writing, reviewing, or refactoring code to avoid overcomplication, make surgical changes, surface assumptions, and define verifiable success criteria.
Review dependency PRs with structured research, existing-PR-discussion capture, multi-lens analysis (security, code quality, impact), and a repeatable verdict template. USE FOR: dependency update PRs, Renovate/Dependabot PRs, library upgrade reviews, "review this dependency PR", "should we merge this update". DO NOT USE FOR: feature PRs, application code reviews, dependency automation/bot configuration, or unattended merge without confirmation.
Refactoring using Remove Parameter in Java Language
Use before merging any change. Use when reviewing code written by yourself, another agent, or a human. Use when you need to assess code quality across multiple dimensions before it enters the main branch.
Trigger when the user requests a review of frontend files (e.g., `.tsx`, `.ts`, `.js`). Support both pending-change reviews and focused file reviews while applying the checklist rules.
Ensure .NET/C# code meets best practices for the solution/project.
Java coding standards for Spring Boot services: naming, immutability, Optional usage, streams, exceptions, generics, and project layout.
Review a pull request diff and write structured feedback to review.json for the workflow to publish. Use when reviewing a checked-out PR from local artifacts like pr_diff.txt and pr_description.txt and producing machine-readable review output instead of posting directly to GitHub.
Python type checking expertise using ty - the extremely fast type checker by Astral. Use when: (1) Adding type annotations to Python code, (2) Fixing type errors reported by ty, (3) Migrating from mypy/pyright to ty, (4) Configuring ty for projects, (5) Understanding advanced type patterns (generics, protocols, intersection types), (6) Setting up ty in editors (VS Code, Cursor, Neovim, PyCharm).
Production Python coding standards with automatic version detection (3.10-3.13). Use when writing, reviewing, or refactoring Python to ensure adherence to modern type syntax, LBYL exception handling, pathlib operations, ABC-based interfaces, and production-tested patterns. Not Dagster-specific - applies to any Python project.
Use after completing a task or before merging. Not for exploring ideas or debugging.