33 boosters for "parallel" — open source, verified from GitHub, ready to install
Enables concurrent investigation of multiple independent tasks by dispatching separate agents to each problem domain, saving time on parallel debugging and testing workflows.
Oh My Opencode is an AI agent harness that provides multi-model orchestration, parallel background agents, and advanced code analysis tools for Claude Desktop and Claude Code. It benefits developers building sophisticated AI-powered applications who need orchestrated agent coordination and deep code understanding capabilities.
"name": "pro-workflow", "description": "Complete AI coding workflow system. Context engineering, agent teams, 18 hook events, 6 agents, 14 skills, 9 guides, cross-agent support, and searchable learnings.", "name": "Rohit Ghumare",
Heuristic scoring (no AI key configured).
Use this agent when documentation in the `architecture/` directory needs to be updated or created for a specific file after implementing a feature, fix, refactor, or behavior change. Launch one instance of this agent per file that needs updating. This agent maintains the *contents* of architecture documentation files — it does not decide which files exist or how the directory is organized.\n\nExamples:\n\n- Example 1:\n Context: A developer just finished implementing OPA policy evaluation in the sandbox system.\n user: "I just finished implementing the OPA engine in crates/openshell-sandbox/src/opa.rs. Update architecture/sandbox.md to reflect the new policy evaluation flow."\n assistant: "I'll launch the arch-doc-writer agent to update the sandbox architecture documentation with the new OPA policy evaluation details."\n <uses Task tool to launch arch-doc-writer with instructions to update architecture/sandbox.md>\n\n- Example 2:\n Context: A refactor changed how the HTTP CONNECT proxy handles allowlists.\n user: "The proxy allowlist logic was refactored. Please update architecture/proxy.md."\n assistant: "Let me use the arch-doc-writer agent to synchronize the proxy documentation with the refactored allowlist logic."\n <uses Task tool to launch arch-doc-writer with instructions to update architecture/proxy.md>\n\n- Example 3:\n Context: After implementing a new CLI command, the assistant proactively updates docs.\n user: "Add a --rego-policy flag to the CLI."\n assistant: "Here is the implementation of the --rego-policy flag."\n <implementation complete>\n assistant: "Now let me launch the arch-doc-writer agent to update the CLI architecture documentation with the new flag."\n <uses Task tool to launch arch-doc-writer with instructions to update architecture/cli.md>\n\n- Example 4:\n Context: A user wants high-level overview documentation for a non-engineering audience.\n user: "Update architecture/overview.md with a non-engineer-friendly explanation of the sandbox system."\n assistant: "I'll launch the arch-doc-writer agent to create an accessible overview of the sandbox system for non-technical readers."\n <uses Task tool to launch arch-doc-writer with audience=non-engineer directive>\n\n- Example 5:\n Context: Multiple files need updating after a large feature lands.\n user: "I just landed the network namespace isolation feature. Update architecture/sandbox.md and architecture/networking.md."\n assistant: "I'll launch two arch-doc-writer agents — one for each file — to update the documentation in parallel."\n <uses Task tool to launch arch-doc-writer for architecture/sandbox.md>\n <uses Task tool to launch arch-doc-writer for architecture/networking.md>
"name": "orchestrator-supaconductor", "description": "Conductor v3 — Multi-agent orchestration with Evaluate-Loop, parallel execution, Board of Directors, and bundled SupaConductor skills for Claude Code", "orchestrator-supaconductor",
"name": "research-council", "description": "Deep research across Claude and Codex in parallel with cross-pollination refinement", "name": "Hamel Husain"
You are a QA validation agent. Execute user stories against web apps using the skill. Walk through each step, screenshot every step, and report a structured pass/fail result. 1. Parse the user story into discrete, sequential steps (support all formats below) 2. Setup — derive a named session from t
"description": "Ship software systematically: project lifecycle, TDD, parallel agents, code review, security auditing, and infrastructure validation", "email": "lgbarn@users.noreply.github.com"
"name": "workflow-orchestrator", "version": "1.14.0", "description": "Delegation system with workflow orchestration, specialized agents, and parallel execution for Claude Code",
Delegates multi-perspective writing feedback by scanning reference materials and launching parallel AI agents to analyze a document through different critical lenses. Useful for writers seeking comprehensive, contextualized feedback on their work.
"description": "Cotask — task management with TASKS.md kanban dashboard", "homepage": "https://github.com/wbopan/cotask", "repository": "https://github.com/wbopan/cotask",
"name": "quantum-loop", "description": "Universal CLI orchestrator with multi-runner support. Autonomous spec-driven development with dependency DAG, parallel worktree execution, two-stage review gates, and modular merge hardening.", "name": "andyzengmath"
"name": "wordpress-expert", "description": "Expert WordPress diagnostics and site builder: structured investigations with intake questioning, site reconnaissance, parallel execution, findings verification, WordPress site generation as Local WP importable zips, and interactive modification sessions."
"name": "cc-godmode", "description": "Self-orchestrating multi-agent development system — 8 specialized AI agents, parallel quality gates, and automated workflows. You say WHAT, the AI decides HOW.", "name": "Dennis Westermann",
Parallel Search MCP enables AI agents to perform concurrent web searches through a standardized MCP server interface. Developers building AI applications on Claude Desktop, Claude Code, or Cursor benefit from faster, more efficient information retrieval for their agents.
"name": "plan-review", "description": "Multi-perspective plan review with VP Product, VP Engineering, and VP Design for implementation plans and architecture proposals.", "name": "Will Smith",
Parallel Task MCP is an MCP server designed to enable deep research and parallel task execution within Claude-based environments. It benefits developers and researchers who need to coordinate multiple concurrent tasks or investigations.
"name": "governance", "description": "Engineering standards and code governance enforcement with parallel agent execution for code reviews, commits, and standards audits.", "name": "Will Smith",
"name": "workflows", "version": "4.77.0", "description": "Development, data science, writing, and workshop presentation workflows with TDD enforcement, output-first verification, agent team parallelization, and GSD-style deviation rules, test gap validation, and session handoff.",
"description": "Multi-model AI plan review: run any acpx-supported agent (Codex, Gemini, Kimi, Qwen, etc.) in parallel, synthesize feedback, debate contradictions", "url": "https://github.com/strml" "homepage": "https://github.com/STRML/cc-debate",
"name": "abstract-to-concrete-design", "description": "Agentic workflow for designers — from abstract problem space to evidence-based design brief. Research, competitive analysis, and UX critique run in parallel to produce a design brief before you open Figma.", "author": { "name": "rizkiridha", "ur
Agent Chatroom MCP Server enables real-time communication and coordination between parallel Claude Code agents, allowing developers to build collaborative multi-agent systems with synchronized messaging and task distribution.
Par5 MCP is a parallel execution server that enables running shell commands and AI agents across lists concurrently, ideal for developers automating batch operations and scaling workflows in Claude and other AI environments.
