By nsheaps
File editing utilities: auto-formatting and linting for written/edited files with project-aware configuration
Modifies files
Hook triggers on file write and edit operations
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npx claudepluginhub nsheaps/ai-mktpl --plugin edit-utilsIntelligent skill that helps Claude parallelize Task tool calls when working on repetitive or batch operations, optimizing throughput based on task complexity
Relentlessly fix a PR until CI passes — iterates through review, fix, push cycles until green
Launch independent Claude sub-agents in tmux sessions with custom configurations, tool restrictions, and iTerm integration
Install and manage 1Password CLI (op) and op-exec in Claude Code sessions. Provides session-start auto-install for web sessions and comprehensive workflow skills.
Automatically syncs todos and plans from ~/.claude/ to the current project's .claude/ directory
Auto-formatting hooks for Python, JavaScript, Markdown, and Bash, plus a guard that blocks force-push and rebase.
Comprehensive code formatting plugin with Prettier integration. Use when you need to format code, validate formatting, or maintain consistent code style. Activates with phrases like 'format my code', 'check formatting', or 'apply code style'. Supports JavaScript, TypeScript, JSON, CSS, Markdown, and many other file types with automatic formatting on file operations.
Auto-configure code quality tools and generate custom /fix command for parallel agent-based fixing
This skill should be used when the model needs to ensure code quality through comprehensive linting and formatting. It provides automatic linting workflows for orchestrators (format → lint → resolve via concurrent agents) and sub-agents (lint touched files before task completion). Prevents claiming "production ready" code without verification. Includes linting rules knowledge base for ruff, mypy, and bandit, plus the linting-root-cause-resolver agent for systematic issue resolution.
Git commit workflow: atomic commits, validation, conventions
Ultra-compressed communication mode. Cuts 65% of output tokens (measured) while keeping full technical accuracy by speaking like a caveman.