「spa」の検索結果

Dispatch and supervise parallel specialist agents with durable task state. Use when automated multi-agent execution is requested.

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-vendor AI image generation with authentication-aware parallel dispatch. Routes to Codex (gpt-image-2 via ChatGPT OAuth) and Pollinations (flux/zimage, free with signup). Gemini provider is present but disabled by default (requires billing). Use for image generation, image creation, visual asset generation, and AI art.

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。

Guides researchers through structured ideation frameworks to discover high-impact research directions. Use when exploring new problem spaces, pivoting between projects, or seeking novel angles on existing work.

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。

Battle-tested PyTorch training recipes for all domains — LLMs, vision, diffusion, medical imaging, protein/drug discovery, spatial omics, genomics. Covers training loops, optimizer selection (AdamW, Muon), LR scheduling, mixed precision, debugging, and systematic experimentation. Use when training or fine-tuning neural networks, debugging loss spikes or OOM, choosing architectures, or optimizing GPU throughput.

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。

Orchestrate multi-agent coding tasks via Claude DevFleet — plan projects, dispatch parallel agents in isolated worktrees, monitor progress, and read structured reports.

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。

Install Codex themes and Codex skin packs with npx skills. Use this skill when a user wants Codex to find, download, validate, apply, switch, remix, or restore Codex desktop themes such as caishen-readable, caishen-lite, mythic-guardian-noir, global-founder-bright, export-night, or caishen-max. It stages verified public-safe theme packs from ChannelerH/codex-skin-packs, checks theme.json/background.png, preserves the native Codex layout, avoids private workspace screenshots, and provides restore guidance.

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。

Design and optimize AI agent action spaces, tool definitions, and observation formatting for higher completion rates.

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。

Dispatch independent tasks to parallel workers or subagents without write collisions. Use when: running or planning agents in parallel, even two; check scopes before any launch.

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: lane contracts, worker-model doctrine, fault tolerance. Triggers: orchestrate, coordinate, agents, parallel, spawn, contract, tier 2, tier 3.

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。

Используй только когда пользователь явно просит запустить Codex Project Autopilot, продолжить проект из .codex-agent или в текущем workspace уже есть активный .codex-agent.

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。

Используй только внутри активного Codex Project Autopilot-проекта, когда пользователь уже запустил автопилот или в workspace есть .codex-agent в фазе discovery/planning.

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 for AI-assisted Unity work that needs live repo discovery, project-derived routing, runtime-owner proof, runtime-visible output hard stops, runtime numeric proof for repeated visible-output failures, state-step guards, multi-agent scope ownership, modular C#/asmdef safety, UI/scene/visual asset gates, data-first content changes, validation, cleanup proof, or durable workflow rules. Best when agents must prove the actual folder/module/scene/prefab/runtime owner before editing, especially runtime UI, generated assets, code graphs, tutorial/state flows, guided selection/action flows, overlay/dim source-bound mistakes, coordinate conversions, focus/highlight/marker/HUD alignment, predictive lead aiming, ballistic trajectories, spatial IoU verification, or repeated "fix still not visible" failures.

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。

Assess an authenticated Agiflow workspace and recommend the right next project-management workflow. Use when a user is new to Agiflow, asks what to do next, needs orientation, or is unsure whether to plan, refine, groom, triage, or review daily status.

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。

Set up Storybook for React Native in Expo, React Native CLI, or Re.Pack projects. Use when adding Storybook to a project, configuring metro.config.js with withStorybook, creating .rnstorybook configuration files, setting up Storybook routes in Expo Router, configuring getStorybookUI, or adding the StorybookPlugin to a Re.Pack rspack/webpack config. Covers Expo, Expo Router, plain React Native CLI, and Re.Pack setups.

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。

Deep strategic research engine — decomposes questions into parallel research threads, spawns multiple agents, and synthesizes into actionable strategic analysis

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。

Set a repo up to prove engineering-task work actually works before it ships. Investigates the repo, ensures a one-command dev stack (`dev-local`) exists, asks whether verification runs locally or in a sandbox (crabbox), confirms/installs the driver (the `playwright-cli` skill for web by default). Outputs three artifacts: a committed `/verify` skill (per-task verification SOP — spawn a verifier sub-agent → drive the app → screenshot/video proof → open a PR with the proof embedded), the `/dev-local` skill + script, and the installed driver skill. Use when someone says "set up verification", "make this repo verifiable", "scaffold a verify skill", "set up the verifier".

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。

Dispatches many independent items in parallel: create a table, fan out to subagents, aggregate results. One row = one unit of work.

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 reviewing a DataFusion Comet pull request that touches memory pools, memory reservations, spilling, the Spark TaskMemoryManager bridge, allocators, or memory-related configuration. Load alongside review-comet-pr.

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 reviewing a DataFusion Comet pull request that adds or changes a Spark expression, its Scala serde, its protobuf message, or its native Rust implementation. Load alongside review-comet-pr, which covers the parts of the review that apply to every PR.

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 an existing Comet expression for correctness and test coverage. Studies the Spark implementation across versions 3.4.3, 3.5.8, 4.0.1, and 4.1.1, reviews the Comet and DataFusion implementations, identifies missing test coverage, and offers to implement additional tests.

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 positioning an American Anthropologist (AA) manuscript against the literature so it reads as a four-field contribution. AA readers span sociocultural, archaeology, biological, and linguistic anthropology, so the paper must engage the conversations they expect and decenter a US/Anglophone-only canon. Stakes the contribution and citational politics; it does not write the lit review.

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 targeting the Journal of Cleaner Production or deciding whether a cleaner-production/sustainability manuscript fits this venue. Encodes the journal's fit, the cleaner-production contribution and methodological-transparency bar, LCA/system-boundary expectations, house style, official-submission re-check, and desk-reject heuristics.

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 positioning an American Educational Research Journal (AERJ) manuscript in the literature. AERJ readers span the whole field, so the paper must engage the literatures a general education-research audience expects and speak past its own subfield. Builds the positioning argument; it does not write the literature review for you.

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 starting or navigating any American Anthropologist (AA) manuscript as the entry point. Routes to the right AA sub-skill based on lifecycle stage, subfield (sociocultural, archaeology, biological, linguistic), and section type (Research Article, Vital Topics Forum, World/Public/Multimodal Anthropologies, Review Essay). It dispatches; it does not draft content.

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。