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概要と使いどころ
Configure and manage Supabase projects using MCP (Model Context Protocol). Use this skill when working with Supabase databases, setting up MCP servers, designing database schemas, implementing Row Level Security, managing migrations, or building modern data architectures with PostgreSQL. Essential for Supabase development, database design, and AI-powered database operations.
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Independent re-derivation gate for proposed changes during autonomous execution. Evaluates a change (code diff, config edit, engine evolution, schema change) against the work's authority matrix and a 4-check protocol: invariant compliance, scope authorization, detection narrowness, and regression risk. Returns structured JSON with pass/fail per check, an overall verdict (APPROVE / REQUEST_CHANGES / REJECT), and blockers. Profile-driven thresholds (strict for unattended runs, lenient for desk supervision). Use when an autonomous agent proposes an engine change, when reviewing a Claude Code-authored modification before merge, or when an unattended profile requires independent re-derivation. Trigger on: "review/approve this proposed change," "critic-gate this," "is this change safe," "is this safe to merge," "should I let this land," "run the critic." Do NOT use for handoff-readiness checks (use rootnode-handoff-trigger-check), general code review, or design-time correctness. Authority matrix required.
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。
Structure-based docking with AutoDock Vina, Vinardo, and AutoDock4 through the Meeko toolchain. Use this skill to define a docking box, prepare receptors and ligands as PDBQT, run single or batch docking, rescore, and interpret affinities, poses, and ligand efficiency. Covers box definition from a reference ligand or pocket residues, protonation and tautomer decisions, flexible side chains, exhaustiveness and seeds, redocking validation, and virtual screening over compound libraries. Also trigger on vina, smina, gnina, mk_prepare_ligand, mk_prepare_receptor, mk_export, scrub.py, PDBQT, autogrid4, docking box, or binding-pose prediction.
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。
Compute relative and absolute binding free energies with the Open Free Energy toolkit — the rigorous alchemical alternative to docking scores when a congeneric series needs reliable potency ranking. Use this skill to plan a perturbation network over a ligand set, choose atom mappings, run hybrid-topology or separated-topology protocols, and analyse the result — per-edge ΔΔG with uncertainty, cycle-closure error, and mean unsigned error against measured affinities. Also trigger on OpenFE, alchemical transformation, thermodynamic cycle, RBFE, ABFE, SepTop, lambda window, MBAR, cycle closure, or perturbation map.
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。
Apple Human Interface Guidelines (HIG) に準拠した iOS アプリの UI を、 単一 HTML ファイルの「実際に動くインタラクティブプロトタイプ」として生成するスキル。 iPhone 15 Pro 相当のデバイスフレーム、ステータスバー、ナビゲーションバー、タブバー、 Inset Grouped リスト、モーダル/シート、アラートを iOS 純正の見た目で再現し、 タップ・スワイプ・入力・画面遷移がすべて動作する状態で出力する。 Claude Design / Artifact でそのまま開ける形式。 Use when: iOS アプリの UI を作りたい、アプリのモック画面が欲しい、 HIG 準拠のデザインを作りたい、iPhone 風のプロトタイプを作りたい、 アプリのデザイン案を可視化したい、App Store 提出用アプリの画面イメージを作りたい。 Triggers: "iOS アプリ UI", "iOS デザイン", "HIG", "Human Interface Guidelines", "iPhone モック", "アプリのモック", "iOS プロトタイプ", "アプリ画面を作って", "iOS UI プロトタイプ", "Claude Design", "ネイティブアプリ風", "アプリのデザイン"
Capture reproducible screenshots from the currently booted iOS Simulator and turn them into three App Store marketing cards with validated dimensions and concise copy. Use after a successful Simulator build, during the two-minute proof lane, or when replacing prototype images with real app captures.
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。
Probe the runtime state of a named feature flag in a CLI binary. Covers the four-pronged evidence protocol (binary strings, live invocation, on-disk state, platform cache), the four-state classification (LIVE / DARK / INDETERMINATE / UNKNOWN), gate-vs-event disambiguation, conjunction-gate handling, and skill-substitution scenarios where a flag appears DARK but the capability is delivered by other means. Use when verifying whether a documented or inferred capability has rolled out, when auditing dark-launched features, or when a prior probe's conclusions need refreshing against a new binary version.
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。
Observe and assess a garden using a structured sensory protocol adapted from Coordinate Remote Viewing. Covers pre-entry clearing (meditate checkpoint), Stage I gestalt impression, Stage II sensory layer (leaf, stem, root, soil), Stage III pattern recognition with AOL management, and garden health triage matrix (heal checkpoint). Use before any intervention, when plants show stress symptoms, at seasonal transitions, when evaluating a new garden site, during regular health monitoring, or after extreme weather events such as frost or heat waves.
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。
Guide viriditas (greening power) meditation and philosophy practice. Covers the concept of viriditas as divine life force, structured meditation protocol, seasonal attunement, and integration with Hildegardian health and spiritual practice. Use when practicing Hildegardian contemplative spirituality, feeling disconnected from seasonal rhythms, experiencing spiritual dryness or lack of vitality, seeking a meditation that integrates body and earth, or deepening understanding of Hildegard's ecological theology.
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。
AI intuitive exploration for approaching unknown codebases, problems, or systems without preconceptions. Adapts the Coordinate Remote Viewing protocol to AI investigation: cooldown (clear assumptions), staged data gathering (raw signals → dimensional → analytical), AOL management (separating observations from premature labels), and structured review. Use when investigating an unfamiliar codebase with unknown architecture, debugging a problem where premature hypotheses could mislead, exploring a domain with limited context, or when previous attempts have been led astray by assumptions and "beginner's mind" would be more productive.
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 an organisation for regulatory inspection by assessing readiness against agency-specific focus areas (FDA, EMA, MHRA). Covers warning letter and 483 theme analysis, mock inspection protocols, document bundle preparation, inspection logistics, and response template creation. Use when a regulatory inspection has been announced or is anticipated, when a periodic self-assessment is due, when new systems have been implemented since the last inspection, or after a significant audit finding that may attract regulatory attention.
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。
Conduct a peer review of research methodology, experimental design, and manuscript quality. Covers methodology evaluation, statistical appropriateness, reproducibility assessment, bias identification, and constructive feedback. Use when reviewing a manuscript, preprint, or internal research report, evaluating a research proposal or study protocol, assessing evidence quality behind a claim, or reviewing a thesis chapter or dissertation section.
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。
Conduct structured insect behavior observations using sampling protocols, ethogram categories, event recording, interaction logging, environmental context, and summary analysis. Covers focal animal sampling, scan sampling, all-occurrences sampling, and instantaneous sampling methods. Defines a standard insect ethogram with locomotion, feeding, grooming, mating, defense, communication, and rest categories. Includes timestamped event recording, intraspecific and interspecific interaction logging, environmental covariate documentation, and time budget analysis. Use when studying insect behavior for ecological research, documenting behavioral repertoires for a species, observing pollinator activity or predator-prey dynamics, or supporting conservation assessments with behavioral 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。
Implement a generative diffusion model (DDPM or score-based) with noise scheduling, U-Net architecture, training loop, and sampling procedures including DDIM acceleration. Use when building a generative model for image, audio, or molecular synthesis; implementing DDPM from a research paper; adding a custom noise schedule or conditioning mechanism; replacing a GAN-based generator with a diffusion alternative; or prototyping before scaling with production frameworks like diffusers.
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 a JSON-RPC 2.0 A2A server with full task lifecycle management (submitted/working/completed/failed/canceled/input-required), SSE streaming, and push notifications. Use when implementing an agent that participates in multi-agent A2A workflows, building a backend for an Agent Card, adding A2A protocol support to an existing agent or service, or deploying an agent that must interoperate with other A2A-compliant agents.
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 an A2A Agent Card (.well-known/agent.json) manifest describing agent capabilities, skills, authentication requirements, and supported content types. Use when building an agent that must be discoverable by other A2A-compliant agents, exposing capabilities for multi-agent orchestration, migrating an existing agent to the A2A protocol, defining the public contract for an agent before implementation, or integrating with agent registries that consume Agent Cards.
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。
Cultivate bonsai trees from species selection through long-term seasonal care. Covers species suitability, structural and maintenance pruning, wiring technique, repotting protocol, soil mix preparation, seasonal care schedules, and contemplative sitting practice. Use when selecting a species for a first or next bonsai, performing structural or maintenance pruning, repotting when roots are circling or growth has stalled, wiring branches for shaping, developing a seasonal care calendar, or building a contemplative practice with a living tree.
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。
Configure MCP (Model Context Protocol) servers for Claude Code and Claude Desktop. Covers mcptools setup, Hugging Face integration, WSL path handling, and multi-client configuration. Use when setting up Claude Code to connect to R via mcptools, configuring Claude Desktop with MCP servers, adding Hugging Face or other remote MCP servers, or troubleshooting MCP connectivity between clients and servers.
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。
Containerize an R-based MCP (Model Context Protocol) server using Docker. Covers mcptools integration, port exposure, stdio vs HTTP transport, and connecting Claude Code to the containerized server. Use when deploying an R MCP server without requiring a local R installation, creating a reproducible MCP server environment, running MCP servers alongside other containerized services, or distributing an MCP server to other developers.
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。
AI internal coordination using stigmergic signals — managing information freshness in context and memory, decay rates for assumption staleness, and emergent coherent behavior from simple local protocols. Use during complex tasks where multiple sub-tasks must coordinate, when context has grown long and information freshness is uncertain, after context compression when information may have been lost, or when sub-task outputs need to feed into each other cleanly without degradation.
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 a parser, protocol, or file format fuzzer stalls at fixed-token validation gates and needs a coverage dictionary. Not for patching the SUT: use fuzzing-obstacles.
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 the user describes an AI workflow gap or uses an ambiguous cross-session reference such as 'the PR Bob mentioned'. Not for tasks that require source or remote-system 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。
Use when deciding what an interface should do before UI is built or audited: consequences, action scope, reachable states, naming, and accessibility. Not for visual implementation: use prototype.
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 /design-variants generates distinct design directions and a gallery for selection. Not for one polished artifact: use polished-web-prototype. Not for token-system picking: use 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。