GitHub - skyiron/crushAIcodingAgent: The glamourous AI coding … — The quickest way to get started is to grab an API key for your preferred provider su
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GitHub - skyiron/crushAIcodingAgent: The glamourous AI coding … — The quickest way to get started is to grab an API key for your preferred provider su
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, deploy, and maintain applications on Hugging Face Spaces — Gradio / Docker / Static SDKs, ZeroGPU and dedicated hardware, model loading, debugging, buckets, inference providers, community grants. Use whenever the user asks to create or host an app on Hugging Face, port code onto ZeroGPU, fix a Space that won't build or run, or otherwise work with `hf spaces …`, `@spaces.GPU`, Space README frontmatter, or the `spaces` Python package.
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 video, music, speech, or images with the operator's MiniMax Token Plan subscription through the codex-router media CLI. Use when the session runs a MiniMax custom (non-OpenAI) model (for example minimax-m3) with the MiniMax Token Plan provider connected, and the user explicitly asks to create a video, a song or music track, spoken audio, or an image. Do not use for reading or analyzing existing media.
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。
React composition patterns that scale. Use when refactoring components with boolean prop proliferation, building flexible component libraries, or designing reusable APIs. Triggers on tasks involving compound components, render props, context providers, or component architecture. Includes React 19 API 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 implementing, integrating, upgrading, debugging, or answering anything involving third-party APIs, libraries, frameworks, CLIs, cloud services, model or provider SDKs, fast-moving product behavior, unfamiliar repo docs or specs, errors that may indicate API drift, or high-stakes auth, security, billing, data, migration, deployment, compliance, or privacy behavior. Forces a docs pass before coding from memory.
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, review, or improve widgets, Live Activities, and controls using WidgetKit and ActivityKit. Use when building home screen, Lock Screen, or StandBy widgets with timeline providers; when creating interactive widgets with Button/Toggle and AppIntent actions; when adding Live Activities with Dynamic Island layouts (compact, minimal, expanded); when building Control Center widgets with ControlWidgetButton/ControlWidgetToggle; when configuring widget families, refresh budgets, deep links, push-based reloads, or Liquid Glass rendering; or when setting up widget extensions, App Groups, and entitlements.
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。
Increase widget visibility on Apple Watch using RelevanceKit. Use when providing contextual relevance signals for watchOS widgets, declaring time-based or location-based relevance, combining multiple relevance providers, or helping the system surface the right widget at the right time on watchOS 26.
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。
Integrate and optimize Core ML models in iOS apps for on-device machine learning inference. Covers model loading (.mlmodelc, .mlpackage), predictions with auto-generated classes and MLFeatureProvider, compute unit configuration (CPU, GPU, Neural Engine), MLTensor, VNCoreMLRequest, MLComputePlan, multi-model pipelines, and deployment strategies. Use when loading Core ML models, making predictions, configuring compute units, or profiling model performance.
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 VoIP calling with CallKit and PushKit. Use when building incoming/outgoing call flows, registering for VoIP push notifications, configuring CXProvider and CXCallController, handling call actions, coordinating audio sessions, or creating Call Directory extensions for caller ID and call blocking.
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 App Intents for Siri, Shortcuts, Spotlight, widgets, Control Center, and Apple Intelligence on iOS. Covers AppIntent actions, AppEntity and EntityQuery models, AppShortcutsProvider phrases, IndexedEntity Spotlight indexing, WidgetConfigurationIntent, SnippetIntent, and assistant schemas. Use when exposing app actions or entities to system surfaces.
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。
Choose OpenRouter models and routers, query live catalog data, use structured outputs and batch inference, and debug routing with metadata. Use when working with OpenRouter APIs, openrouter/auto, openrouter/free, model discovery, pricing, providers, batch jobs, or structured JSON responses.
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。
Set up and configure WorkOS AuthKit authentication with Convex backend. Use when integrating AuthKit, configuring JWT providers, setting up environment variables, or implementing sign in and sign out flows with React and Vite. Supports Netlify deployment.
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。
Sets up Convex auth, identity mapping, and access control. Use for login, auth providers, users tables, protected functions, or roles in a Convex app.
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。
Multi-agent autonomous startup system for Claude Code. Triggers on "Loki Mode". Orchestrates 100+ specialized agents across engineering, QA, DevOps, security, data/ML, business operations, marketing, HR, and customer success. Takes PRD to fully deployed, revenue-generating product with zero human intervention. Features Task tool for subagent dispatch, parallel code review with 3 specialized reviewers, severity-based issue triage, distributed task queue with dead letter handling, automatic deployment to cloud providers, A/B testing, customer feedback loops, incident response, circuit breakers, and self-healing. Handles rate limits via distributed state checkpoints and auto-resume with exponential backoff. Requires --dangerously-skip-permissions flag.
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。
Harden Kubernetes Role-Based Access Control by implementing least-privilege policies, auditing role bindings, eliminating cluster-admin sprawl, and integrating external identity providers.
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Assesses organizational readiness for post-quantum cryptography migration per NIST FIPS 203/204/205 standards. Performs cryptographic inventory scanning to identify quantum-vulnerable algorithms (RSA, ECDH, ECDSA), evaluates hybrid TLS configurations with X25519MLKEM768, and validates CRYSTALS-Kyber (ML-KEM) and CRYSTALS-Dilithium (ML-DSA) readiness. Implements crypto-agility assessment using oqs-provider for OpenSSL. Use planning yaparken or executing the transition from classical to post-quantu...
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。
bu skill covers Dağıt:ing HashiCorp Vault for centralized secrets management across cloud environments, including dynamic secret generation for databases and cloud providers, transit encryption, PKI certificate management, and Kubernetes integration. It addresses eliminating hardcoded credentials from application code and CI/CD pipelines by implementing short-lived, automatically rotated secrets.
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。
bu skill covers implementing Okta as a centralized identity provider for cloud environments, configuring SSO integration with AWS, Azure, and GCP, Dağıt:ing phishing- resistant MFA with Okta FastPass, managing lifecycle automation for user provisioning and deprovisioning, and enforcing adaptive access policies based on device posture and risk signals.
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 SOC 2 Type II audit preparation including gap assessment against AICPA Trust Services Criteria (CC1-CC9), evidence collection from cloud providers and identity systems, control testing validation, remediation tracking, and continuous compliance monitoring. Covers all five TSC categories (Security, Availability, Processing Integrity, Confidentiality, Privacy) with automated evidence gathering from AWS, Azure, GCP, Okta, GitHub, and Jira. Use when preparing for or maintaining SOC 2 Ty...
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。
Deploy a new LLM model via LiteLLM (GitOps) and/or Azure (Terraform + node backend), add it to the ai toolkit, create the required pull requests, and verify end-to-end. Use when rolling out a model to any environment, adding a model to the toolkit, troubleshooting "model not available" errors, or finding pricing/token limits/model ids for any provider.
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。
Execute model inference on GPU cloud providers. Handles code generation, deployment, execution, and result collection across HF Inference API/Endpoints, Colab, Modal, beam.cloud, Vast.ai, and RunPod. Use when running models on GPU, deploying to cloud, executing notebooks, or troubleshooting GPU execution failures. Triggers on "run on GPU", "execute model", "deploy to modal", "colab notebook", "beam deploy", "HF inference", "HF endpoints", "vast", "runpod".
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。
Busabase-backed App-in-Skill dashboard for a shared LLM gateway's cost and model governance — daily spend trend, cost breakdown by service/model, a canary-rollout status board, and a deterministic cost/error anomaly list. Use when the user invokes $kelly-llm-gateway or /kelly-llm-gateway, or wants to review LLM gateway spend, model routing, canary rollouts, rollback readiness, or cost/error anomalies for services routed through one shared gateway to multiple LLM providers/models. Human actions (promote/rollback/hold a rollout, acknowledge an anomaly) write directly onto the route's own Busabase record — this skill never changes a real routing config.
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。
Busabase-backed App-in-Skill money ledger for aggregating Mercury, Stripe, Airwallex, and Creem accounts into a read-only dashboard. Use when the user invokes $kelly-money or /kelly-money, wants a total cashflow ledger, account columns, Accounts sidebar, Account Detail views, finance onboarding, connector setup, transaction import/sync, reconciliation, balances, payouts, payments, fees, refunds, transfers, or a review of money movement across these providers.
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。
Digital-human implementation and demo skill for choosing, prototyping, and QA-ing low-cost 2D photoreal digital humans and high-control 3D custom digital humans. Use when the user wants a digital-human avatar, AI host, customer-service presenter, multimodal voice-to-lip-sync video stream, vendor comparison for services such as Silicon Intelligence / Tencent Zhiying / ZEGO-like real-time providers, or a UE/Unity 3D digital-human architecture and launch-ready demo.
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。