Search Results for "parallel-execution" | AgentCC

sapiom-deploy

Deploy and run code on Sapiom — scheduled jobs, batch execution, sandboxes. Use when user says "deploy this", "ship it", "run this on a schedule", "put this on a cron", "run these tasks in parallel", "spin up a server", "I need a dev environment", or already has a script and wants it running in the cloud.

implementing-in-background

Orchestrates multiple AI agents (Claude, Codex, Gemini) for parallel implementation in the background. Separates independent tasks from planning docs, each agent writes code directly. Context-safe with auto-save. Use for "백그라운드 구현", "bg impl", "병렬 구현", "Codex로 구현", "구현해줘", "코드 작성해줘" requests.

implementationbackgroundparallel-execution+4

sub-agents

Execute external CLI AIs as isolated sub-agents for task delegation, parallel processing, and context separation. Use when delegating complex multi-step tasks, running parallel investigations, needing fresh context without current conversation history, or leveraging specialized agent definitions. Returns structured JSON with agent output, exit code, and execution status.

workflow-orchestration

Coordinate structured thinking and multi-agent parallel execution for complex tasks. Use when tackling multi-step projects, planning parallel work, breaking down complex problems, coordinating specialist tasks, facing architectural decisions, or when user mentions "workflow", "orchestration", "multi-step", "coordinate", "parallel execution", "structured thinking", "break this down", "plan this out", "how should I approach", or needs help planning complex implementations.

task-decomposer

Breaks down large features into implementable tasks with dependency mapping, edge case identification, test strategy planning, and phased execution order. Produces task tables with effort sizing, parallelization flags, and risk flags for each phase. Triggers on: "break down this feature", "decompose", "task breakdown", "how should I implement", "implementation plan", "what are the steps for", "edge cases for", "plan this feature", "implementation steps", "break this into tasks", "work breakdown", "project breakdown". Use this skill when a feature or project needs to be broken into actionable steps.

planning-in-background

Orchestrates multiple AI agents (Claude, Codex, Gemini) for parallel planning in the background with auto-save. Agents continue running even when session hits context limits. Use for "백그라운드 기획", "bg plan", "병렬 기획", "멀티 AI 기획", "기획해줘", "N명이 기획", "계획", "플래닝", "plan", "설계" requests.

planningbackgroundparallel-execution+4

task-decomposition

Break down complex tasks into parallel workstreams for efficient execution. Use when planning multi-component features, large refactors, or any work that benefits from parallelization.

parallel-tasks

Creates multiple git worktrees and launches parallel Claude sessions for simultaneous task execution. Maximum 3 tasks.

Infinite Gratitude

agent-skills-hub

Multi-agent research skill for parallel research execution (10 agents, battle-tested with real case studies).

parallel-claude

Launch multiple Claude Code instances in parallel using tmux and git worktrees to tackle beads tasks concurrently. Use when user mentions parallel execution, multi-agent, parallel claude, or wants to run multiple Claude instances simultaneously on different tasks.

multi-agent-orchestrator

Marketing multi-agent orchestration system for complex, parallelizable campaigns. Coordinates specialized AI agents for: (1) Research + synthesis + content creation pipelines, (2) Platform-specific content generation at scale (Reddit, LinkedIn, Twitter, Email), (3) Lead generation and outbound campaigns, (4) Human-in-the-loop review before any external execution, (5) Automated posting with natural timing patterns. Triggers: "build me a marketing team", "orchestrate agents", "outbound campaign", "multi-platform content", "lead generation system", "social media blitz", or any request implying coordinated marketing specialist work.

workflow-automation

agent-skills-hub

Workflow automation is the infrastructure that makes AI agents reliable. Without durable execution, a network hiccup during a 10-step payment flow means lost money and angry customers. With it, workflows resume exactly where they left off. This skill covers the platforms (n8n, Temporal, Inngest) and patterns (sequential, parallel, orchestrator-worker) that turn brittle scripts into production-grade automation. Key insight: The platforms make different tradeoffs. n8n optimizes for accessibility

Dev Workflow Orchestrator

Full development workflow from idea to parallel execution. Use when planning features/bugfixes/refactors, breaking work into beads tasks, selecting tasks to parallelize (max 4), launching Claude instances in tmux worktrees, and cleaning up after completion. Triggers: "plan feature", "plan refactor", "plan bugfix", "start parallel work", "launch parallel", "cleanup worktrees", "kill parallel", or /dev-workflow.

worker-dispatch

Use to spawn isolated worker processes for autonomous issue work. Uses Task tool with run_in_background for parallel execution and TaskOutput for monitoring. Pre-extracts context to minimize worker token usage.

infinite-gratitude

Multi-agent research skill for parallel research execution (10 agents, battle-tested with real case studies).

web-frameworks

Build modern full-stack web applications with Next.js (App Router, Server Components, RSC, PPR, SSR, SSG, ISR), Turborepo (monorepo management, task pipelines, remote caching, parallel execution), and RemixIcon (3100+ SVG icons in outlined/filled styles). Use when creating React applications, implementing server-side rendering, setting up monorepos with multiple packages, optimizing build performance and caching strategies, adding icon libraries, managing shared dependencies, or working with TypeScript full-stack projects.

parallelize

Use when planning parallel execution of independent tasks via subagents or concurrent tool calls; for workflow planning or throughput optimization.

sub-agent-delegation

Delegate complex tasks to sub-agents for parallel autonomous work. Use when GPU kernel optimization, numerical correctness verification, performance profiling, or long-running validation would benefit from focused independent execution.

web-frameworks

Build modern full-stack web applications with Next.js (App Router, Server Components, RSC, PPR, SSR, SSG, ISR), Turborepo (monorepo management, task pipelines, remote caching, parallel execution), and RemixIcon (3,100+ SVG icons in outlined/filled styles). Use when creating React applications, implementing server-side rendering, setting up monorepos with multiple packages, optimizing build performance and caching strategies, adding icon libraries, managing shared dependencies, or working with TypeScript full-stack projects.

LangGraph Execution Control

Invoke this skill for LangGraph workflows, parallel execution, interrupts, or streaming. Covers the Send API for fan-out, interrupt() for human-in-the-loop pauses, Command for resuming, and stream modes (values/updates/messages).

Goose

Parallel agent orchestration using Goose recipes. USE WHEN user wants to spawn agents, run recipes, review code, generate tests, refactor, roast code, security audit, or any autonomous development task. Supports non-blocking parallel execution.

sub-agents

Execute external CLI AIs as isolated sub-agents for task delegation, parallel processing, and context separation. Use when delegating complex multi-step tasks, running parallel investigations, needing fresh context without current conversation history, or leveraging specialized agent definitions. Returns structured JSON with agent output, exit code, and execution status.

build-ci-cd-pipeline

Design and implement multi-stage CI/CD pipelines using GitHub Actions with matrix builds, dependency caching, artifact management, and secret handling. Create workflows that span linting, testing, building, and deployment stages with parallel execution and conditional logic. Use when setting up automated testing and deployment for a new project, migrating from Jenkins or CircleCI to GitHub Actions, implementing matrix builds across platforms, adding build caching, or creating multi-stage pipelines with security scanning and quality gates.

delegate

Smart delegation that analyses tasks and routes to parallel or sequential execution

Swarm Orchestration

Orchestrate multi-agent swarms with agentic-flow for parallel task execution, dynamic topology, and intelligent coordination. Use when scaling beyond single agents, implementing complex workflows, or building distributed AI systems.

build-ci-cd-pipeline

Design and implement multi-stage CI/CD pipelines using GitHub Actions with matrix builds, dependency caching, artifact management, and secret handling. Create workflows that span linting, testing, building, and deployment stages with parallel execution and conditional logic. Use when setting up automated testing and deployment for a new project, migrating from Jenkins or CircleCI to GitHub Actions, implementing matrix builds across platforms, adding build caching, or creating multi-stage pipelines with security scanning and quality gates.

n8n Workflow Generator

Generates JSON blueprints for n8n Cloud workflows from natural-language descriptions. Use when Claude needs to create, modify, or compose n8n workflows programmatically. Includes a complete schema of nodes and connections, parallel execution patterns, context-maintenance strategies, and modular templates for AI workflows, RAG pipelines, and legal automations.

practical-ai-leadership-skill-testing

Practical-AI-Leadership

This skill should be used when the user asks to "test skill", "test skill determinism", "verify skill consistency", "check skill outputs", "run skill test", "compare skill runs", "validate skill before release", "check for execution issues", or wants to ensure a skill produces consistent results. Uses tmux for true parallel CLI testing. Not for integration-testing the simpleclub-skills CLI tool — use dev-simpleclub-skills-integration-test for that.

multi-agent-workforce-planner

organvm-iv-taxis

Designs parallel agent workstreams for large feature sets by analyzing dependencies, assigning specialized agent types (Explore, Plan, Bash, Edit), maximizing parallelization, and creating execution plans with progress tracking and failure recovery. Use when breaking down large features into parallel agent work.

multi-agentparallelplanning+2

infinite-gratitude

Multi-agent research skill for parallel research execution (10 agents, battle-tested with real case studies).

parallel-retrospective

Analyze completed parallel workflows for lessons learned. Use when: reviewing workflow execution quality, identifying process improvements, evaluating skill effectiveness, post-mortem analysis after parallel work, assessing planning accuracy. Triggers: retrospective, review, post-mortem, lessons learned, workflow analysis, evaluate parallel, workflow quality, planning assessment.

sub-agents-doc

Reference documentation for Claude Code subagents -- creating and configuring specialized AI assistants with custom system prompts, tool restrictions, permission modes, model selection, persistent memory, lifecycle hooks, foreground/background execution, and patterns for delegation, context isolation, parallel research, and chaining.

multi-agent-patterns

Kalyanikhandare29

This skill should be used when the user asks to "design multi-agent system", "implement supervisor pattern", "create swarm architecture", "coordinate multiple agents", or mentions multi-agent patterns, context isolation, agent handoffs, sub-agents, or parallel agent execution.

qa-sourcerank

Full QA cycle for SourceRank AI with swarm-parallel persona testing: discover bugs via 4 concurrent virtual user personas on production, generate CTO/CPO reports, fix issues via /qa-fix, verify via /qa-verify, detect regressions. True parallel execution via TeamCreate swarm. Uses psql for QA issue tracking in SourceRank Supabase DB. Triggers on: qa sourcerank, sourcerank qa, test sourcerank, qa cycle sourcerank.

axiom-testing-async

Use when testing async code with Swift Testing. Covers confirmation for callbacks, @MainActor tests, async/await patterns, timeout control, XCTest migration, parallel test execution.

parallel-execution

Patterns for parallel subagent execution using Task tool with run_in_background. Use when coordinating multiple independent tasks, spawning dynamic subagents, or implementing features that can be parallelized.

polars

Fast in-memory DataFrame library for datasets that fit in RAM. Use when pandas is too slow but data still fits in memory. Lazy evaluation, parallel execution, Apache Arrow backend. Best for 1-100GB datasets, ETL pipelines, faster pandas replacement. For larger-than-RAM data use dask or vaex.

oneplan

OnePlan is a GitHub-native, context-driven engineering workflow using Milestones (tracks), Issues (spec/plan), and Sub-issues (phases/tasks). Use for complex features/bugfixes that need structured planning, resumable execution, parallel tasks, and team coordination.

Research-Driven Debugging

Research-driven debugging workflow that combines web research for similar cases, deep code analysis with task-planner-analyzer, and iterative fixes with modular-code-architect and code-reviewer. Use when encountering training collapse, gibberish generation, or architecture-level bugs where the problem may be documented in research literature. Parallel execution of research and fixes for efficiency.

zo-swarm-orchestrator

Spawn parallel agent teams with token optimization, hierarchical memory, and resilient execution. v4 adds token-aware memory strategies to prevent context-window exhaustion.

shipkit-dev-plan

stefan-stepzero

Breaks a framework spec into implementation steps with file ownership, dependencies, and phase gates. Outputs a plan compatible with shipkit-dev-team for parallel execution. Use after running shipkit-dev-spec.

playwright-testing

End-to-end testing with Playwright using role-based locators, auto-waiting, network mocking, visual regression, fixtures for test isolation, parallel execution, CI integration, authentication state reuse, and trace viewer debugging. Use when building reliable browser automation tests that catch regressions before production.

processing-api-batches

Optimize bulk API requests with batching, throttling, and parallel execution. Use when processing bulk API operations efficiently. Trigger with phrases like "process bulk requests", "batch API calls", or "handle batch operations".

vitest-performance

Use when vitest performance optimization including fast execution, watch mode, and parallelization strategies.

Parallel Planner

fatih-developer

Analyze multi-step tasks to identify which steps can run in parallel, build dependency graphs, detect conflicts (write-write, read-write, resource contention), and produce optimized execution plans. Triggers on 3+ independent steps, "speed up", "run simultaneously", "parallelize", "optimize" or any task where sequential execution wastes time.

NotebookLM Master Research Assistant

A professional-grade skill for automating complex research, data synthesis, and content generation using Google NotebookLM. Supports deep research, parallel execution, and Obsidian integration.

multi-agent-patterns

Use this Skill when a user asks to "design multi-agent system", "implement supervisor pattern", "create swarm architecture", "coordinate multiple agents", or otherwise mentions multi-agent patterns, context isolation, agent handoffs, sub-agents, or parallel agent execution.

claw-multi-agent

OpenClaw multi-agent parallel orchestration system that makes AIs collaborate like a team. Supports parallel research, multi-model comparison, code pipelines and other scenarios, and has been proven to save 50–65% of time in practice. Trigger keywords: multi-agent, multiple agents, parallel execution, multi-model comparison, subtask distribution, parallel research, commander mode, run multiple AIs simultaneously.