Use this skill when you writing commands, hooks, skills for Agent, or prompts for sub agents or any other LLM interaction, including optimizing prompts, improving LLM outputs, or designing production prompt templates.
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。
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概要と使いどころ
Use this skill when you writing commands, hooks, skills for Agent, or prompts for sub agents or any other LLM interaction, including optimizing prompts, improving LLM outputs, or designing production prompt templates.
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。
Automates interactions for Apple-platform apps (iOS, tvOS, macOS) and Android devices. Use when navigating apps, taking snapshots/screenshots, tapping, typing, scrolling, or extracting UI info across mobile, TV, and desktop targets.
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。
Build a community management playbook for a brand's social media channels. Use when asked to create guidelines for managing comments, DMs, and community interactions, define a moderation policy, or build response frameworks for social media community managers. Produces a complete playbook with response templates, escalation paths, moderation rules, and tone guidelines.
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。
Help users build a sustainable habit of regular customer interaction to ensure product development is driven by real-world needs rather than internal assumptions.
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 designing, changing, or reviewing user-facing interfaces or interaction flows, including API changes that alter visible states or recovery. Backend-only work without user-facing effects stays on its existing route.
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。
Define or review a visual system, DESIGN.md, or redesign direction. Use for typography, layout, color, motion, and interaction design decisions.
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。
Visually validate an interactive CLI or terminal UI in Codex's in-app browser using a real local PTY, fixed rendering, keyboard interaction, screenshots, and session evidence. Use for TUI layout changes, terminal menus, colors, prompts, resize behavior, keyboard flows, or proof-of-work where Codex would otherwise reach for Computer Use or a desktop terminal. Do not use for desktop-terminal-emulator-specific behavior or ordinary non-interactive command output.
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。
Produce and continuously maintain ONE living review document for a multi-item session — a cockpit header (Progress checklist, Working folder, Context) plus per-item review cards that you approve or request changes on directly in the doc or side panel. Use whenever a session has multiple deliverables you need to review/approve (meeting-processing + planning, multi-ticket work, briefs with several drafts, any "do X, then plan/draft Y and Z"). The doc is the interaction surface: you edit it (or reply in chat) to approve/change; the agent keeps it live as work progresses.
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 as the entry point for any Agricultural Systems (AgSy) manuscript. Routes to the right AgSy sub-skill based on where you are in the lifecycle and which article type (research paper, short communication, perspective, comment, review) fits. AgSy is a systems-science journal, so the router's first job is to confirm there is a real systems question — interactions, hierarchical levels, trade-offs — not a single-factor field trial. 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。
Use when building figures and tables for an Agricultural Systems (AgSy) manuscript so exhibits communicate interactions, dynamics, trade-offs, and model performance clearly. AgSy is a systems journal, so the best exhibits show trade-off frontiers, observed-vs-simulated fit, resource flows, and conceptual system diagrams — not just a bar chart of one treatment. Designs exhibits; it does not run the 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。
Use when deciding whether a project fits Agricultural Systems (AgSy) and which article type to target. AgSy is a systems-science journal, so the test is a genuine systems question — interactions among components, across hierarchical levels (field → farm → landscape → region → food system), trade-offs, and emergent behavior — analyzed with integrated modelling, NOT a single-factor field trial. Helps frame the question; it does not collect data.
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 building or cleaning the tables and figures for an Academy of Management Journal (AMJ) manuscript — correlation tables, regression/SEM/HLM result tables, the theoretical-model figure, and interaction plots in AOM house style. Finalizes exhibits; it does not run the analysis (amj-data-analysis) or frame the contribution (amj-contribution-framing).
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 designing or auditing AAMAS experiments - self-play and population-based training, opponent selection, equilibrium and regret metrics, game-theoretic simulations, ablations, seeds, hyperparameters, compute, and claim-to-evidence fit - with emphasis on experiments that probe the interaction rather than chase a single-agent leaderboard.
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 deciding whether a project is a strong AAMAS fit, comparing AAMAS with AAAI, IJCAI, NeurIPS, ICML, EC, and the JAAMAS journal, identifying whether the agents are truly the research object, naming the interaction primitive (solution concept, mechanism, coordination, negotiation), and sharpening the multiagent framing before writing begins.
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 revising an AAMAS paper so the interaction contribution leads the first page, the solution concept or incentive property is named, the game and agents are legible, claims are paired with proofs or multiagent experiments, the argument fits eight two-column pages plus references, and the wording stays double-blind.
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 strengthening AAMAS reproducibility evidence for interaction claims, including proofs and game definitions, opponent and population sets, self-play protocols, random seeds, compute, uncertainty on strategic outcomes, baselines, and consistency between what the paper claims about agents and what the artifact can actually show.
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 working with the Associate Editor and Editor of an Academy of Management Annals (Annals) review — scope alignment after a proposal is invited, what review-article referees evaluate, and revision expectations. Plans the interaction; it does not run the portal preflight (amann-submission) or draft the response letter (amann-revision).
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 explaining or planning around AAMAS peer review, covering OpenReview review release, the double-blind rebuttal on preliminary reviews, area-chair discussion, the mixed game-theory, MARL, and systems reviewer pool, the public posting of reviews and decisions, and how acceptance criteria weigh the interaction contribution.
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 packaging AAMAS multiagent code, environments, opponent and population sets, random seeds, game definitions, and logs as anonymous supplementary evidence or a public post-acceptance release, even without a separate artifact badge, so that game-theory and MARL reviewers can inspect and re-run the interaction claims.
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。
Compose screen and interaction traps: navigation, adaptive layout, window insets, pagers, toolbars, sheets, list drag and selection, sliders, text fields, settings UI, one-shot effects. Use when layout, gestures or navigation misbehave.
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 Project Osmos for long-running Fabric and OneLake data-engineering outcomes, including task status, messages, follow-ups, cancellation, and deletion. Osmos tasks are remote service tasks, not local background agents. In Fabric portal Copilot, direct interaction is unsupported; point users to GitHub Copilot CLI. Use spark-cli for direct non-Osmos Spark work. Triggers: "Project Osmos", "Project Osmos task status", "check my Osmos task".
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。
Write a street-interview ad from a complete inspected commercial interaction and current brand facts. Render product guessing, or prepare mic-only, prepared-sample or visible-task conversation script/prompt previews. Premise, actions and ad connection vary; capture rules stay fixed. Conversation media delivery is unverified.
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。
Write UI tests for Blazor applications (Server or WebAssembly) using Playwright. Covers navigation, interaction, authentication, selectors, and common Blazor-specific patterns.
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。
Write unit and integration tests for Akka.NET actors using modern Akka.Hosting.TestKit patterns. Covers dependency injection, TestProbes, persistence testing, and actor interaction verification. Includes guidance on when to use traditional TestKit.
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。