33 boosters for "parallel" — open source, verified from GitHub, ready to install
"name": "cms-cultivator", "description": "14 specialist agents + 24 commands + 14 skills for Drupal/WordPress. Agents orchestrate comprehensive quality checks with parallel execution. Design-to-code workflows with browser validation. CSV export for PM tools. Drupal.org contribution integration. Drup
"description": "Orchestrates Hamster Studio brief execution with team personas, parallel wave execution, and deep review modes. Ship, plan, review, QA, and retro — all from Claude Code.", "url": "https://tryhamster.com" "homepage": "https://tryhamster.com",
Helps developers plan and set up Git worktrees for parallel task execution by generating organized branch and worktree paths based on AGENTS.md conventions. Useful for teams managing multiple concurrent development efforts.
Automates git worktree creation and management with iTerm2 integration, enabling developers to work on multiple features in parallel with isolated development environments across tabs and windows.
Smith is a feedback validation agent that uses parallel research sub-agents to rigorously critique code feedback and plans, ideal for teams needing systematic validation of technical reviews.
Automates git worktree creation and management with iTerm2 integration, enabling developers to work on multiple features in parallel with isolated environments opened in separate terminal tabs or windows.
A knowledge curation agent that researches, validates, and determines optimal storage methods (URL reference, local excerpt, or embedding) for information sources using parallel web scraping. Ideal for AI engineers building knowledge-intensive agent systems who need intelligent source evaluation and integration.
Automates git worktree creation and management with iTerm2 integration, enabling developers to work on multiple features in parallel with isolated environments. Ideal for teams using iTerm2 who need streamlined worktree workflows.
A specialized agent that intelligently researches, validates, and categorizes knowledge sources for AI systems, determining optimal storage methods (URL references, local extracts, or embeddings) using parallel web scraping. Ideal for developers building knowledge-intensive agent systems who need automated source curation and validation.
