Automated multi-agent orchestrator that spawns CLI subagents in parallel, coordinates via MCP Memory, and monitors progress. Use for orchestration, parallel execution, and automated multi-agent workflows.
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概要と使いどころ
Automated multi-agent orchestrator that spawns CLI subagents in parallel, coordinates via MCP Memory, and monitors progress. Use for orchestration, parallel execution, and automated multi-agent workflows.
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Write publication-ready ML/AI/Systems papers for NeurIPS, ICML, ICLR, ACL, AAAI, COLM, OSDI, NSDI, ASPLOS, SOSP. Use when drafting papers from research repos, structuring arguments, verifying citations, or preparing camera-ready submissions. Includes LaTeX templates, reviewer guidelines, and citation verification workflows.
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。
Generate Ian-style Xiaohei illustrations for articles, posts, blogs, Notion documents, workflows, methods, processes, structures, states, metaphors, and opinions. Use when the user asks for weird, hand-drawn, Xiaohei, article, editorial, body illustrations, illustration ideas, shot lists, title removal, image edits, or image regeneration. By default, all image text and annotations are English, even when the source article is Chinese; only use another language when the user explicitly asks.
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Use when multiple workflows duplicate the same operational logic, when deciding what belongs in actions vs shared services, or when refactoring repeated operational blocks across domain flows. Use when adding new features that share mechanics with existing ones.
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Build a source-derived writing style profile from real posts, essays, launch notes, docs, or site copy, then reuse that profile across content, outreach, and social workflows. Use when the user wants voice consistency without generic AI writing tropes.
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Regression testing strategies for AI-assisted development. Sandbox-mode API testing without database dependencies, automated bug-check workflows, and patterns to catch AI blind spots where the same model writes and reviews 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。
Use before expensive VidSeeds MCP workflows - seeds, daily MCP call quotas, async jobId polling, when to call vidseeds_get_seed_balance, and avoiding retry loops on MCP_QUOTA_EXCEEDED or insufficient seeds.
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Use for VidSeeds MCP thumbnail workflows - generate, poll jobs, edit, restyle, Thumbnail Studio (trends, briefs, subjects, overlay text), apply to a project, publish to YouTube, or thumbnails from a local video file via vidseeds-local.
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Use for VidSeeds MCP project workflows - create a project from YouTube, list/get/snapshot, regenerate metadata (sync or async), translate metadata, apply thumbnails, and update per-platform config before publish.
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Use only after explicit Codex `$superloopy:superloopy-research` or Claude Code `/superloopy:superloopy-research` invocation, a research task started with a leading `loopy` or `루피` (such as `loopy research`), or an active Superloopy loop explicitly routing a research deliverable here. Evidence-backed Superloopy research orchestration with automatic advisory usage targets, parallel read-only lanes, per-retrieval verdicts, graded and dated sources, empirical verification, a priced claim ledger, cited synthesis, and optional reports. Do not activate from research, investigate, look-up, summarize, deep-dive, report, or similar vocabulary alone, in any language; ordinary questions, debugging, and implementation context-gathering stay with their primary workflows.
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Eval-Driven Development (EDD) for AI workflows. pass@k metrics, capability evals, regression evals. Triggers: eval, edd, pass@k, capability, regression, benchmark.
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Registry fallback entry point for the VidSeeds.ai MCP connector. Use the bundled domain skills for setup, efficiency, thumbnails, projects, analytics, local video, and publishing workflows.
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。
Search Mouser Electronics for electronic components — secondary source for prototype orders. Find parts, check pricing/stock, download datasheets, analyze specifications. Use with KiCad for BOM creation and part selection. Also supports batch MPN-list seeding (`--mpn-list`) for bulk datasheet workflows without a KiCad project. Use this skill when the user specifically mentions Mouser, when DigiKey is out of stock or has worse pricing, when comparing prices across distributors, or when searching for parts that DigiKey doesn't carry. For package cross-reference tables and BOM workflow, see the `bom` skill.
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Search LCSC Electronics for electronic components — find parts by LCSC number (Cxxxxx) or MPN, check stock/pricing, download datasheets, analyze specifications. Sister company to JLCPCB, same parts library. Sync and maintain a local datasheets directory for a KiCad project, or use batch MPN-list seeding (`--mpn-list`) for bulk workflows without a project. No API key needed — uses the free jlcsearch community API. Use this skill when the user mentions LCSC, JLCPCB parts library, JLCPCB assembly parts, production sourcing, Cxxxxx part numbers, needs to find LCSC equivalents for parts, is preparing a BOM for JLCPCB assembly, or wants to download datasheets and LCSC is available. For package cross-reference tables and BOM workflow, see the `bom` skill.
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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.
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Search Newark, Farnell, and element14 for electronic components — find parts by MPN or distributor part number, check pricing/stock, download datasheets, analyze specifications. One unified API covers all three storefronts (Newark for US, Farnell for UK/EU, element14 for APAC). Free API key, simple query-parameter auth, no OAuth. Datasheets download directly from farnell.com CDN with no bot protection. Sync and maintain a local datasheets directory for a KiCad project, or use batch MPN-list seeding (`--mpn-list`) for bulk workflows without a project. Use this skill when the user mentions Newark, Farnell, element14, needs parts from a non-US distributor, wants to compare pricing across regions, or needs datasheets from a source that doesn't require complex API auth. For package cross-reference tables and BOM workflow, see the `bom` skill.
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。
INVOKE THIS SKILL when implementing human-in-the-loop patterns, pausing for approval, or handling errors in LangGraph. Covers interrupt(), Command(resume=...), approval/validation workflows, and the 4-tier error handling strategy.
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Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends AIPex's capabilities with specialized knowledge, workflows, or tool integrations.
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Provider reference for collecting public profiles, posts, comments, transcripts, trends, and ad-library data from major social platforms through ScrapeCreators. Use as a dependency of research workflows, not as the final user-facing deliverable.
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Create LinkedIn carousel posts as high-quality PNG images. Design informational multi-slide posts like "5 AI GTM workflows" with consistent styling, then automatically screenshot each slide at LinkedIn's optimal 1080x1080px format.
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Set up signal capture for a Simulink Real-Time application using `slrealtime.Instrument`. Use when choosing which signals a real-time application captures and where the data goes — test-pointing or canvas-badging a signal before build (`TestPoint`, `DataLogging`), constructing an Instrument from an `.mldatx`, calling `addSignal`, `addInstrumentedSignals`, `addFileLogSignals`, `validate`, `connectCallback`, `copy`, or `generateScript`, attaching an instrument to `tg.Instruments` via `addForFileLog`, `addForSDI`, or `addForMATLAB`, setting up live-streaming signals, dynamic file-log workflows, or persisting an instrument as M-code. Selects and routes signals only — not for configuring, building, running, or connecting applications onto targets.
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Configure Simulink models for Embedded Coder (ERT), Simulink Coder (GRT rapid-prototyping), or AUTOSAR code generation. Use when the user asks to generate embedded C or C++ code, run a full build of a model, produce a code generation report, configure a model for production/ECU deployment or rapid-prototyping code, target ARM or x86 hardware, apply MISRA C/C++ compliance (ERT/AUTOSAR only — Simulink Coder does not ship MISRA profiles), or set up GRT, ERT, AUTOSAR, or shared-library targets. Handles target selection, hardware mapping, model hierarchy propagation, and constraint introspection via the configure_for_codegen function. Do NOT use for GRT shared-library variants (grt_malloc.tlc), DDS, or ROS, or for iterative optimization workflows that measure baseline metrics, apply targeted changes, and re-measure to confirm improvement.
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Use this skill to run multiple Simulink simulations in parallel with parsim, batchsim, and DesignStudy. TRIGGER when: user asks for parameter sweep, sweeping/varying parameters across simulations, Monte Carlo study, batch simulation, running multiple simulations, parallel simulations, large-scale multiple simulations, any task involving repeated simulations with different parameter values, user mentions having an existing script/function for parameter sweeps, or user wants to migrate from parfor/set_param/for-loop patterns to recommended workflows.
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。
Manages MATLAB projects for Simulink workflows: path management, file registration, labels, source control configuration, and project lifecycle. Use when creating projects, adding models/dictionaries/requirements to projects, configuring labels for automation, fixing broken model references, or setting up source control for Simulink artifacts.
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。