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概要と使いどころ
Write and debug spreadsheet formulas (Excel/Google Sheets), pivot tables, and array formulas; translate between dialects; use when users need working formulas with examples and edge-case checks.
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 authoring Litestar skill content, Python/TypeScript examples, PEP 604, async I/O, Google docstrings, ruff/mypy/pyright, pytest, or CI rules. Not for focused Litestar APIs.
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。
Runs a team of 50 LLM personas through a 30-round structured debate to predict market direction. Uses the Canvas Agent Swarm Service — the same shared infrastructure other skills use for smaller agent teams. Output is an influence-weighted consensus direction + trade recommendation with a transparent record of every argument, research query, and cross-examination.
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。
Implement proven backend architecture patterns including Clean Architecture, Hexagonal Architecture, and Domain-Driven Design. Use when architecting complex backend systems or refactoring existing applications for better maintainability.
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。
Stage whole files, selected hunks, or selected lines in Git without interactive prompts. Use when preparing an exact commit boundary while preserving unrelated working-tree changes.
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。
Creates a Beads issue for a requested piece of work, completes exactly that work, and closes the issue. Use when the user invokes `/bx` or `$bx`, or asks for a bead to be created and the described work done in the same go. For creating a bead without doing the work, use the `bc` skill instead.
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。
Look up word definitions, pronunciations, parts of speech, and usage examples from the Free Dictionary API.
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。
Drafts a Certificate of Incumbency certifying current officers, directors, and signing authority for a U.S. corporation. Covers exact legal name matching, incumbency tables with specimen signatures, board resolution certification, authority limitations, reliance language, and execution formalities. Use when banks, lenders, investors, or counterparties require verification of corporate authority for closings, financings, or transactions.
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。
Comprehensive legal applications skill covering civil/criminal/administrative litigation workflows, trial defense strategies, legal document drafting (complaints, answers, appeals, retrial petitions, enforcement applications, representation opinions, defense statements, legal opinions, etc.), arbitration (commercial & labor), mediation, enforcement procedures, evidence rules, and litigation risk assessment. Trigger when users ask about: lawsuit/litigation/trial, legal documents, court defense, evidence/cross-examination, arbitration, enforcement, legal strategy, filing a case, appeal, retrial, representation, pleading, or any legal procedural 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。
Manages Rule 30(b)(6) corporate representative deposition workflows — drafting notice topics with reasonable particularity, building examination outlines, defending designees, handling objections, and preserving binding admissions for summary judgment or trial. Use when drafting or responding to 30(b)(6) notices, selecting and preparing designees, building topic-by-topic outlines, or triaging scope and privilege disputes. Trigger keywords: 30(b)(6), corporate representative deposition, topic list, designee, notice analysis, deposition objections, corporate admissions.
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 taking and defending Rule 30(b)(6) corporate representative depositions. Drafts topic lists with reasonable particularity, builds examination outlines for binding corporate admissions, analyzes noticed topics for objections, and prepares designees. Use when drafting 30(b)(6) notices, preparing corporate deposition topics, selecting or preparing designees, or defending corporate representative depositions.
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。
Loads, lists, composes, or validates graded evaluation rubrics: PASS/WARN/FAIL grading with weighted criteria and balanced anchor examples for evaluator-style review.
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Turn a raw idea into ONE honest recommendation: interview one question at a time until the problem, requirements, goals, non-goals, and constraints are CONFIRMED, then deliver a single verdict — do, don't, cheaper alternatives, trade-offs, ordered checklist, success metrics. Required: the user wants exactly ONE recommendation — not options, not a debate — and their framing is open to challenge (advise may answer a different question than the one asked). Triggers on "what should I do about X", "advise me on X", "am I approaching this right", "is this the right move". Do NOT use to be interrogated with no recommendation (→ mk:grill) — advise also interviews one question at a time, but only to reach a verdict. Do NOT use when the framing is settled and only the options are open (→ mk:brainstorming). Do NOT use to decide whether something is worth building (→ mk:office-hours). Do NOT use when you want several perspectives to argue it out (→ mk:party).
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。
Structured second-pass reasoning after code review or plan evaluation. Offers named reasoning methods (pre-mortem, inversion, red team, Socratic, etc.) to re-examine findings through a specific lens. Use after /mk:review verdict or any time deeper analysis is needed on an existing output. NOT for initial review (see mk:review); NOT for creating implementation plans (see mk:plan-creator).
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 a grounded Human Design BodyGraph and whole-chart reading from exact birth data. Use for Human Design charts, BodyGraph, decisions, profile, channels, talents, work, wealth, relationships, mission, or chart-based follow-up questions. Supports Chinese and English.
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。
Store and semantically search agent memory with ONNX vector embeddings on a ruOS desktop, using the Ruflo CLI. Use to persist patterns/decisions across sessions and recall them by meaning rather than exact key.
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。
Prepare, submit and reconcile reviewed Fusion Automation jobs with exact sources, scoped authorization and explicit budgets. Not for arbitrary model-generated cloud scripts.
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 shadcn components and projects — adding, searching, fixing, debugging, styling, and composing UI, including chat interfaces. Provides project context, component docs, and usage examples. Applies when working with shadcn/ui, component registries, presets, --preset codes, or any project with a components.json file. Also triggers for "shadcn init", "create an app with --preset", or "switch to --preset".
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。
Comprehensive reference for inter-process communication mechanisms -- every way processes can talk on a computer. Covers sockets (TCP, UDP, Unix domain), WebSockets, SSE, pipes (named/anonymous), shared memory (mmap, shm_open), message queues, signals, D-Bus, XPC (macOS), gRPC, REST, stdin/stdout, file-based coordination, and clipboard. Performance benchmarks, platform availability, and code examples for each. Special focus on which IPC works best for AI agent coordination. Activate on: "IPC", "inter-process communication", "process communication", "how do I talk between processes", "Unix socket vs TCP", "shared memory", "named pipe", "WebSocket vs SSE", "gRPC vs REST", "agent coordination IPC", "XPC service", "message passing", "stdout pipe", "D-Bus", "mmap". NOT for: distributed systems design (use distributed-systems), network protocol design (use networking), message queue infrastructure like Kafka (use data-pipeline-engineer).
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 Kafka consumer groups that survive rebalances, hit the right delivery guarantee (at-most/at-least/exactly-once), and handle poison messages without stalling the topic. Use when picking a partition assignment strategy (Range vs Sticky vs Cooperative-Sticky vs the new KIP-848 protocol), tuning heartbeat / session / max.poll.interval timeouts, choosing manual vs auto offset commits, designing dead-letter or retry topics, or migrating from Classic to the next-gen Consumer protocol. NOT for Kafka cluster ops (broker tuning, partition reassignment), schema design (Avro/Protobuf/Schema Registry), or stream processing topology (use a kafka-streams 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。
Implementing the `Idempotency-Key` HTTP header pattern (Stripe-pioneered, IETF-standardizing) so retries don't double-charge or duplicate side effects — full Postgres schema with recovery-point state machine, fingerprint check, in-progress lock with 409 response, and 24h retention. Grounded in Stripe blog/docs, the IETF httpapi WG draft, and Brandur Leach's canonical implementation.
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。
Apply practical DAG decomposition, transitive-edge reduction, and reachability indexing to dense dependency graphs. Use when low width and repeated queries justify preprocessing. NOT for cyclic graphs, one-off graph checks, or exact-minimum-chain requirements.
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。
Metal/wgpu/WGSL shader surfaces for native Rust gpui apps (Zed-family, pd-console), stockpiled with beautiful copy-pasteable shader-toy examples. Use for custom GPU fragment passes behind/around gpui panes: ocean/water shaders, pixelated waves and boats, a living harbor, dithered chrome borders, sonar sweeps, aurora/starfields, CRT/scanline post. Trigger on: wgsl, wgpu, metal shader, gpui shader, shadertoy, fragment shader, SDF, noise/fbm, ordered dithering, pixelation, render-to-texture, "pixelated waves and boats", living harbor water. NOT for: web/GLSL/three.js shaders (use a web tool), non-shader gpui motion (use rust-gpui-motion), general GUI layout/color (use beautiful-gui-design), CLI/TUI (use beautiful-cli-design).
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。
Generates production-ready design tokens from natural language descriptions. Outputs Tailwind configs, CSS custom properties, and DTCG W3C tokens from 24 trends + 31 AI-ready styles with 2800+ component examples.
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。