kiro-spec-batch
FreeCreate complete specs (requirements, design, tasks) for all features in roadmap.md using parallel sub-agent dispatch by dependency wave.
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1.4K skills · sorted by relevance
Create complete specs (requirements, design, tasks) for all features in roadmap.md using parallel sub-agent dispatch by dependency wave.
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Expert guidance for Fully Sharded Data Parallel training with PyTorch FSDP - parameter sharding, mixed precision, CPU offloading, FSDP2
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Serves LLMs with high throughput using vLLM's PagedAttention and continuous batching. Use when deploying production LLM APIs, optimizing inference latency/throughput, or serving models with limited GPU memory. Supports OpenAI-compatible endpoints, quantization (GPTQ/AWQ/FP8), and tensor parallelism.
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Provides PyTorch-native distributed LLM pretraining using torchtitan with 4D parallelism (FSDP2, TP, PP, CP). Use when pretraining Llama 3.1, DeepSeek V3, or custom models at scale from 8 to 512+ GPUs with Float8, torch.compile, and distributed checkpointing.
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Use when: User wants to run Archon workflows, CREATE workflows or commands, set up Archon, or manage Archon configuration. Triggers (run): "use archon to", "run archon", "archon workflow", "use archon for", "have archon", "let archon", "ask archon to". Triggers (create): "create a workflow", "write a workflow", "make a command", "author a workflow", "new workflow", "new command", "archon workflow yaml". Triggers (setup): "set up archon", "install archon", "how to use archon", "configure archon", "archon setup", "get started with archon". Triggers (config): "change my archon config", "modify archon config", "archon config", "change archon settings", "update my config", "help me change my config", "edit archon config", "archon configuration". Triggers (init): "initialize archon", "set up .archon", "archon init", "add archon to repo". Capability: Runs AI workflows in isolated git worktrees for parallel development. Also: Creates and manages workflow YAML files, command files, and configuration. NOT for: Direct Claude Code work - only for delegating to Archon CLI.
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Comprehensive end-to-end validation of the Archon Web UI using browser automation and codebase review. Use when: User wants to validate, test, or audit the Archon web interface, find UI/UX bugs, test workflow management, verify parallel agent orchestration, or run comprehensive browser-based E2E tests. Triggers: "validate ui", "test the ui", "e2e test", "browser test", "validate archon", "test archon ui", "ui audit", "ux review", "comprehensive test", "validate everything". Capability: Starts Archon, runs exhaustive browser automation tests via agent-browser CLI, performs codebase review, and produces a detailed bug/UX report. NOT for: Unit tests (use `bun test`), CLI-only validation (use /validation:validate-simple).
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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.
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15-agent hierarchical mesh coordination for v3 implementation. Orchestrates parallel execution across security, core, and integration domains following 10 ADRs with 14-week timeline.
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Deep agentic-flow@alpha integration implementing ADR-001. Eliminates 10,000+ duplicate lines by building claude-flow as specialized extension rather than parallel implementation.
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Launch, inspect, or tear down an isolated fleet of ready SDD Composy tasks: one branch and Git worktree per member, a bound LOOP, cmux/tmux/headless presentation, no automatic merge. Use to run several ready tasks in parallel — 'rodar várias tarefas em paralelo', 'lançar o fleet', 'fleet status', 'tear down member X'. Do NOT use for a single task (sdd-execute, sdd-loop) or for merging without the explicit teardown token.
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Use when approved phases should run in parallel — visually in a cmux panel or unattended — when fleet status is requested, or when a fleet member must be stopped or merged
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Launch, inspect, and tear down autonomous phase fleets in isolated Git worktrees, on the Codex or the Claude runtime. Use when approved Flow phase slugs should run in parallel, when fleet status is requested, or when a fleet member must be stopped or explicitly merged.
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Build modern Next.js 13+ applications using App Router architecture with Server Components, Client Components, and advanced routing patterns. Use when implementing server-first rendering, creating nested layouts, building parallel routes, implementing intercepting routes, using React Server Components, optimizing data fetching with server-side async components, implementing streaming with Suspense, managing client-side interactivity boundaries, or leveraging Next.js 13+ app directory features for performant, SEO-friendly React applications.
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天才会議の並列サブエージェント版。最重要の意思決定で、4人のペルソナを独立したサブエージェントとして並列実行し、互いの意見を見ずに独立思考させてから統合・レッドチーム検証する。「並列会議」「本気の会議」「独立に考えさせて」「エージェント会議」などのリクエストで使用。
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Guides Rust performance optimization. Use when profiling, benchmarking, reducing allocations, improving cache locality, choosing between rayon/async/threads, or applying SIMD/parallelism.
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Use only when the user explicitly types `/orchestrate goal` to decompose a large task, spawn a tree of parallel cloud-agent workers/subplanners/verifiers via the Cursor SDK, and collect structured handoffs; do not invoke autonomously.
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Multi-agent exploration and task delegation for complex areas of interest. Use when you need to deeply explore a codebase area, gather information from multiple perspectives, or delegate parallel research tasks for comprehensive analysis.
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Idiomatic Go concurrency - sync primitives, channel semantics, the select statement, and the standard channel patterns (cancellation/done-channel, fan-out/fan-in, pipeline, or-done, context, worker-pool). Use when writing or reviewing Go that spawns goroutines, shares state, or coordinates over channels, even if the user never says "concurrency" - e.g. data races, deadlocks, goroutine leaks, sync/context/select usage, or "make this parallel". Distilled from luk4z7/go-concurrency-guide.
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Research a skill domain before building or improving a skill. Searches academic papers, practitioner blogs, and GitHub skill repos in parallel to find current best practices, domain gotchas, and existing skill patterns. Called by universal-skill-creator and improve-skills before writing any skill. Also load directly when the user asks to research a domain for a skill, find existing skills on a topic, discover best practices for a skill, check what research exists before building an agent skill, or says "what does current research say about", "find best practices for".
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Structure git work with atomic commits, conventional messages, short-lived branches, and pre-commit hygiene. Load when committing, branching, resolving merge conflicts, organizing parallel work, or reviewing git history. Also triggers on "git workflow", "commit message", "conventional commits", "atomic commit", "branch strategy", "git worktree", "how should I commit this". Does not replace project-specific hook policies — complements them.
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Internal skill. Called by setup-evaluation after a PASS. Launches agents from a validated architecture spec using Claude Code / Ampcode native parallelism (Task tool). Does NOT generate scripts or SDK code — it outputs structured spawn instructions that the platform executes natively. Never invoked directly by the user. Never launches without a setup-evaluation PASS.
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Design state-of-the-art multi-agent systems, orchestration patterns, and wiring from scratch. Load when the user asks to build an agent system from scratch, design agent orchestration patterns, choose between sequential/parallel/hierarchical workflows, or define how multiple agents should collaborate. Also triggers on "agent architecture", "multi-agent wiring", "agent orchestration pattern", "how to connect these agents", "design the communication structure". Called by agent-builder for complex topologies (>4 agents or hierarchical). For process-driven agent design, use agent-builder instead.
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Master Bevy's Entity Component System (ECS) in Rust, covering Systems, Queries, Resources, and parallel scheduling.
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Azure Batch SDK for Java. Run large-scale parallel and HPC batch jobs with pools, jobs, tasks, and compute nodes.
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