「nda」の検索結果

Map and attack the authentication, authorization, session, tenant, federation, and machine-identity boundaries of a system, proving whether access controls actually hold rather than whether they appear to. Use whenever work touches login, sessions, tokens, roles, permissions, multi-tenancy, password reset, invitations, OAuth/OIDC/SAML, API keys, service accounts, webhooks, admin impersonation, or any question of "can this actor do or see this thing." Prefer this over a generic security pass for identity-heavy surfaces. Part of the audit suite; inherits the shared constitution while its own job is proving or disproving access boundaries.

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TidyFactor Design track — code-native UI design lifecycle engine (Figma alternative). Supports all 7 stages of UI design (Discovery, Foundation, Architecture, Components, Motion, Quality, Delivery) with zero per-page CSS/JS and zero build step. Pluggable CSS foundations (Native, Tailwind utility-first, daisyUI, Hybrid, shadcn, Pico, Bootstrap, Alpine) and full Arabic/RTL support (El Messiri/Tajawal, never Amiri above 24px). Trigger on commands "study", "brief", "init", "brand", "typography", "school", "tokens", "palette", "assets", "layout", "nav-footer", "components", "page", "dashboard", "motion", "states", "flow", "i18n", "perf", "audit", "clone", "retrofit", "handoff", "deploy", or requests like "build a design system", "UI design lifecycle", "prototype this website", "Figma alternative", "نموذج أولي تفاعلي", "صمّم لوحة تحكم".

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。

Review the changes since a fixed point (commit, branch, tag, or merge-base) along two axes: Standards (does the code follow this repo's documented coding standards?) and Spec (does the code match what the originating issue/spec asked for?). Runs both reviews in parallel sub-agents and reports them side by side. Use when the user wants to review a branch, a PR, work-in-progress changes, or asks to "review since X".

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Implement NFT standards (ERC-721, ERC-1155) with proper metadata handling, minting strategies, and marketplace integration. Use when creating NFT contracts, building NFT marketplaces, or implementing digital asset systems.

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。

Universal coding standards, best practices, and patterns for TypeScript, JavaScript, React, and Node.js development.

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 editing an existing codebase and the goal is minimal, standard, and non-invasive changes — prioritizes simplest solution, standard libraries first, and surgical modification without unsolicited refactors

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Personal CRM built on monday.com. Tracks contacts, last interactions, next meetings, and topics. Runs daily to update from Calendar + email. Delivers pre-meeting briefings as part of morning-briefing. Use when: someone asks about a contact, before a meeting, or during daily CRM sync.

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Schedule meetings, parse meeting notes, extract action items. Three distinct intents covered. Invoke when user mentions a specific meeting (past or future) by name or context. NOT for general calendar checks (use direct calendar.py), NOT for time-zone math. Triggers: "schedule with X", "minutes of the X meeting", "action items from yesterday's meeting", "prep me for meeting with X".

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OpenClaw API gateway proxy for authenticated SaaS calls (100+ services in references/SERVICES.md). Use ONLY when making an HTTP request to a third-party service that requires the gateway's stored credentials. NOT for direct API calls with bearer tokens already in scope, NOT for monday.com (use monday-for-agents), NOT for WhatsApp (use heleni-whatsapp). Triggers: "call the X API", "fetch from <service>", "send to Slack via gateway", "use the gateway for".

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Decide where to save any piece of information — monday.com, local file, daily notes, or MEMORY.md. Use this skill before saving anything to ensure the right destination. Prevents local clutter and ensures the owner can access all relevant content in monday.com.

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Use when building, updating, or styling any monday Builders presentation, slide deck, internal pitch, kickoff doc, or HTML deliverable that should match the official Builders brand. Provides the canonical color palette, typography, gradient stroke, cover decorations, card patterns, and layout primitives sourced from the 2026 Builders Kickoff master deck. Invoke when user mentions "Builders deck", "Builders style", "match the deck", "make it on-brand", "kickoff style", or asks to design a slide/page that should look like internal monday Builders material.

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Systematic strategic planning framework for philosophy and interdisciplinary academic papers targeting preprint platforms (PhilArchive, arXiv, PhilSci-Archive). Use when users want to: (1) plan a paper on a specific topic, (2) identify research gaps and assess originality, (3) develop optimized paper outlines, (4) prepare for preprint submission, or (5) understand platform requirements and writing standards. Triggered by phrases like 'plan a paper on,' 'help me design a paper about,' 'identify research gaps in,' 'is this idea original,' or when users need structured research planning. The skill guides through three phases: Platform Analysis (identifying target venue and studying sample papers), Theoretical Framework (AI-driven literature search and gap identification), and Outline Optimization (structured design with reviewer-perspective self-assessment). Each phase includes quality evaluation standards and validation checkpoints.

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AI demos and GPU compute with Gradio Spaces and Hugging Face Spaces ZeroGPU. Use when writing or reviewing code that uses `@spaces.GPU`, configuring `python_version` or `requirements.txt` for a ZeroGPU Space, or handling ZeroGPU-specific code constraints — pickle-based process isolation, `gr.State` semantics across the worker boundary, no `torch.compile` (use AoTI instead), CUDA wheel-only builds (no `nvcc` at build or runtime), large vs xlarge sizing, and dynamic duration callables. Make sure to use this skill whenever the user mentions ZeroGPU, `@spaces.GPU`, or the `spaces` Python package, or hits ZeroGPU-specific code errors like `PicklingError` across the worker boundary, `illegal duration`, or `flash-attn` wheel-build failures — even when the user does not explicitly ask for ZeroGPU coding guidance. Trigger on `import spaces` or `@spaces.GPU` in 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。

Build or update a professional-grade design system in Figma from a codebase. Use when the user wants to create variables/tokens, build component libraries, create individual components with proper variant sets and variable bindings, set up theming (light/dark modes), document foundations, or reconcile gaps between code and Figma. Also use when the user asks to create or generate any component in Figma — even a single one — since components require proper variable foundations, variant states, and design token bindings to be production-quality. This skill teaches WHAT to build and in WHAT ORDER — it complements the `figma-use` skill which teaches HOW to call the Plugin API. Both skills should be loaded together.

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Official NVIDIA-authored guidance for NVIDIA cuDF GPU DataFrames, pandas acceleration, dask-cuDF, ETL, joins, groupby, CSV/Parquet I/O, nullable semantics, and multi-GPU DataFrame workloads.

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。

Expert en data science (pandas, numpy, scikit-learn, feature engineering, model selection)

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。

Data Scientist IA — Expert en data science (pandas, numpy, scikit-learn, EDA, feature engineering, statistical 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。

Content strategist v3 — content pillars, editorial calendar, distribution, repurposing

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。

Clean architecture v3 — use cases, entities, interfaces, dependency inversion, testing, boundaries

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。

Review the changes since a fixed point (commit, branch, tag, or merge-base) along two axes - Standards (does the code follow this repo's documented coding standards?) and Spec (does the code match what the originating issue/spec asked for?). Runs both reviews in parallel sub-agents and reports them side by side. Use when the user wants to review a branch, a PR, work-in-progress changes, or asks to "review since X".

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。

ScalarDBの制約を考慮したデータモデル設計を行います。Partition Key・Clustering Key・Secondary Index の設計、ホットスポット評価、メタデータオーバーヘッド見積もり、バックエンドDB選定を含みます。ワークフローStep 04（データモデル設計）で使用します。

When setting up telemetry, debugging distributed systems, or standardizing application output.

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Xcode 26 and Apple platform update notes with a focus on Liquid Glass, Foundation Models Framework, and Apple Intelligence. Use when asked to explain, summarize, compare, or implement Xcode 26 era framework changes across SwiftUI, UIKit, AppKit, Foundation, App Intents, StoreKit, MapKit, WidgetKit, visionOS, or Swift language features.

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Integrate on-device AI using Foundation Models framework, Core ML, and open-source LLM runtimes on Apple Silicon. Covers Foundation Models (LanguageModelSession, @Generable, @Guide, SystemLanguageModel, structured output, tool calling), Core ML (coremltools, model conversion, quantization, palettization, pruning, Neural Engine, MLTensor), MLX Swift (transformer inference, unified memory), and llama.cpp (GGUF, cross-platform LLM). Use when building tool-calling AI features, working with guided generation schemas, converting models, or running on-device inference.

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。