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概要と使いどころ
Use when long-running or parallel agent work must respect 5-hour and weekly usage limits by checking usage between waves, pausing near the cap, and resuming only when the window is clear.
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Use when acting as the multi-project orchestrator and lead coordinator across repositories using the Agent Orchestrator (AO) daemon. Spawns, inspects, coordinates, and reviews parallel coding agents in isolated Git worktrees.
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Multi-agent SWE team built on the Workshop model. Full-stack vertical workers, meeting room with @mention notification, private pipes, shared task board. Git worktree isolation, Leader-driven coordination. Mixed Codex/Claude Code engine. Use when a task needs engineering depth beyond a single agent. NOT for simple task parallelism (use agent-task-orchestration) or design discussions (use agent-brainstorm).
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Task decomposition and multi-agent orchestration with retry, checkpoint recovery, and real-time monitoring. Mixed Codex/Claude Code engine. Parallel/sequential execution.
日本語の概要は準備中です。原文の説明を表示しています。
Expert guidance for Swift Testing: test structure, #expect/#require macros, traits and tags, parameterized tests, test plans, parallel execution, async waiting patterns, and XCTest migration. Use when writing new Swift tests, modernizing XCTest suites, debugging flaky tests, or improving test quality and maintainability in Apple-platform or Swift server projects.
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Parallel read-only multi-agent root-cause investigation for bugs, regressions, crashes, flaky behavior, or unexplained failures. Use when the user asks to investigate a bug, find the root cause, trace a regression, understand why something broke, or wants a ranked diagnosis with the fastest proof path without making code edits.
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Plan and execute large refactor or rewrite efforts efficiently with parallel multi-agent analysis and implementation. Use when a user asks to refactor many files, split workstreams, analyze a target code area, and coordinate sub-agents with clear ownership and dependency-aware execution.
日本語の概要は準備中です。原文の説明を表示しています。
Audit Xcode project configuration, build settings, scheme behavior, and script phases to find build-time improvements with explicit approval gates. Use when a developer wants project-level build analysis, slow incremental builds, guidance on target dependencies, build settings review, run script phase analysis, parallelization improvements, or module-map and DEFINES_MODULE configuration.
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Generates as many digits of pi as possible and writes them into files inside a tokenMaxxing/ folder. Use when the user asks to token-maxx, fill a file with pi digits, test agent output throughput, or generate N pi files sequentially or in parallel.
日本語の概要は準備中です。原文の説明を表示しています。
Spawn N parallel candidates at the same task, pick a base, graft the strongest parts of the losers into it. Use for /arena, 'arena this', 'throw it in the arena', or when one attempt at a non-trivial artifact would lock in the wrong shape.
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Use for 'why does X work this way', 'why we picked Y', design rationale, regressions, postmortems, or data-backed thresholds. Discovers available MCPs and queries each evidence category (source control, issue tracker, long-form docs, real-time chat, infrastructure observability, error tracking, product analytics warehouse) in parallel, then returns a cited read on decisions and tradeoffs. Use how for runtime behavior.
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Periodic pass that keeps a project's verification skill and feature map honest: parallel source readers per feature, one live session driving every feature, at most one PR of proven corrections. Use for /maintain-verification-skill or "audit the verify skill".
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This skill should be used when the user asks how to "use VibeTags", "add VibeTags annotations", "set up AI guardrails", "protect code from AI", "configure AI platforms", asks about @AILocked, @AIContext, @AIDraft, @AIAudit, @AIIgnore, @AIPrivacy, @AICore, @AIPerformance, @AIContract, @AITestDriven, @AIThreadSafe, @AIImmutable, @AIDeprecated, @AIObservability, @AIRegulation, @AIArchitecture, @AILegacyBridge, @AIStrictClasspath, @AIInternationalized, @AIPublicAPI, @AISchemaSafe, @AIStrictExceptions, @AIStrictTypes, @AIParallelTests, @AIIdempotent, @AIFeatureFlag, @AISecure, @AICallersOnly, @AISandboxOnly, @AIMemoryBudget, @AIPure, @AIDomainModel, @AIExtensible, @AIInputSanitized, @AISecureLogging, @AIExplain, @AIPrototype, @AISunset, @AITemporary annotations, or wants to control how AI tools interact with Java code.
日本語の概要は準備中です。原文の説明を表示しています。
Control Herdr, a terminal multiplexer for coding agents. Use only when the user explicitly mentions Herdr or asks to use Herdr to inspect or control panes, tabs, workspaces, commands, or another agent. Do not use merely because a task could benefit from a background terminal, delegation, or parallel work. Requires HERDR_ENV=1.
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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
日本語の概要は準備中です。原文の説明を表示しています。
Multi-agent orchestration patterns. Use when multiple independent tasks can run with different domain expertise or when comprehensive analysis requires multiple perspectives.
日本語の概要は準備中です。原文の説明を表示しています。
Multi-agent autonomous startup system for Claude Code. Triggers on "Loki Mode". Orchestrates 100+ specialized agents across engineering, QA, DevOps, security, data/ML, business operations, marketing, HR, and customer success. Takes PRD to fully deployed, revenue-generating product with zero human intervention. Features Task tool for subagent dispatch, parallel code review with 3 specialized reviewers, severity-based issue triage, distributed task queue with dead letter handling, automatic deployment to cloud providers, A/B testing, customer feedback loops, incident response, circuit breakers, and self-healing. Handles rate limits via distributed state checkpoints and auto-resume with exponential backoff. Requires --dangerously-skip-permissions flag.
日本語の概要は準備中です。原文の説明を表示しています。
Use when facing 2+ independent tasks that can be worked on without shared state or sequential dependencies
日本語の概要は準備中です。原文の説明を表示しています。
Expert in CrewAI - the leading role-based multi-agent framework used by 60% of Fortune 500 companies. Covers agent design with roles and goals, task definition, crew orchestration, process types (sequential, hierarchical, parallel), memory systems, and flows for complex workflows. Essential for building collaborative AI agent teams. Use when: crewai, multi-agent team, agent roles, crew of agents, role-based agents.
日本語の概要は準備中です。原文の説明を表示しています。
Master Bevy's Entity Component System (ECS) in Rust, covering Systems, Queries, Resources, and parallel scheduling.
日本語の概要は準備中です。原文の説明を表示しています。
Azure Batch SDK for Java. Run large-scale parallel and HPC batch jobs with pools, jobs, tasks, and compute nodes.
日本語の概要は準備中です。原文の説明を表示しています。
You are an API mocking expert specializing in realistic mock services for development, testing, and demos. Design mocks that simulate real API behavior and enable parallel development.
日本語の概要は準備中です。原文の説明を表示しています。
Decomposes a large implementation plan into small-model-sized tasks executed by supervised worker agents (e.g. Haiku) in dependency-ordered parallel waves, with a plan-first approval gate inside every task, file-based state for context compaction, and a hard escalation ladder. Use when a master plan or multi-workstream feature is too large for one session and should be executed cheaply by many small agents under frontier-model supervision.
日本語の概要は準備中です。原文の説明を表示しています。
Review the changes since a fixed point (commit, branch, tag, or merge-base) along two axes - Standards (does the code follow this repo's documented coding standards?) and Spec (does the code match what the originating issue/spec asked for?). Runs both reviews in parallel sub-agents and reports them side by side. Use when the user wants to review a branch, a PR, work-in-progress changes, or asks to "review since X".
日本語の概要は準備中です。原文の説明を表示しています。