Configures JWT Bearer authentication for .NET APIs. Includes token generation, validation, refresh tokens, and user context extraction from claims.
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概要と使いどころ
Configures JWT Bearer authentication for .NET APIs. Includes token generation, validation, refresh tokens, and user context extraction from 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。
Use the Crabbox wrapper for OpenClaw remote validation across Linux, macOS, Windows, and WSL2, including delegated Blacksmith Testbox proof. Report the actual provider and id.
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 a model training pipeline — algorithm selection, cross-validation, and serialization. Use when asked to "train a model for this", "design a training pipeline", or "which algorithm should we use".
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 asked about UX patterns, interaction best practices, form design, navigation patterns, or loading states. Examples: "best practice for form validation", "navigation pattern for dashboard", "loading state UX"
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。
Audit existing data cleaning code — find missing validation, silent data loss, and quality gaps. Use when asked to "audit our data cleaning", "are we losing data silently", or "find data quality gaps".
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。
Survey existing forecasting code or models in a codebase — find gaps, stale models, and missing validation. Use when asked "what forecasting models do we have", "audit our forecasts", or "find stale models".
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Advanced TanStack Query (v5) expert. Covers useSuspenseQuery, infinite scrolling, optimistic mutations, SSR/React Server Components hydration, and advanced cache invalidation / Pakar manajemen state asinkron menggunakan TanStack Query (React Query) v5 dan Next.js App Router (SSR).
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 guide for multi-pass autonomous AI code self-review — syntax validation, logic correctness, architectural conformance, security audit, and performance analysis without external tooling — enabling the agent to catch its own errors before presenting code / Panduan ahli review kode otonom multi-pass oleh AI — validasi sintaks, kebenaran logika, konformitas arsitektur, audit keamanan, dan analisis performa tanpa tooling eksternal — memungkinkan agen menangkap errornya sendiri sebelum menampilkan kode.
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。
Helper text, placeholders, validation and submit behaviour. Use when designing or reviewing a form, input field or data entry UI.
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。
Few semantic colours, each meaning one thing, and errors with a way forward. Use when designing status indicators, validation, alerts or error states.
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。
Merges GitHub Pull Requests after validating pre-merge checklist. Use when user wants to merge PR, close PR, finalize PR, complete merge, approve and merge, or execute merge. Runs pre-merge validation (tests, lint, CI, comments), confirms with user, merges with proper format, handles post-merge cleanup.
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 GitHub Pull Requests with automated validation and task tracking. Use when user wants to create PR, open pull request, submit for review, or check if ready for PR. Analyzes commits, validates task completion, generates Conventional Commits title and description, suggests labels. NOTE - for merging existing PRs, use github-pr-merge 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。
Integrate MDMA into an application and build features with it — wire up parsing, the runtime store, React rendering, LLM streaming, custom components, prompts, and CI validation. Use this skill when the user asks to add MDMA to an app, build a chat that streams MDMA, author or maintain a custom prompt, validate MDMA documents, register a custom component, or expose MDMA to an agent via MCP. Generates focused, correct wiring that uses the right packages for the job instead of reinventing them.
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Real-world problem formulation, mathematical abstraction, and applied mathematics for translating between practical problems and mathematical frameworks. Covers the modeling cycle (problem identification, assumptions, formulation, analysis, validation, interpretation), Polya's framework adapted for modeling, common model types (linear, exponential, logistic, periodic, power-law), dimensional analysis (Buckingham Pi theorem), optimization (linear programming, gradient descent, constraint satisfaction), probability models (Markov chains, queuing theory, Monte Carlo simulation), statistical modeling (regression, hypothesis testing, model selection), model criticism (overfitting, underfitting, sensitivity analysis), and real-world case studies. Use when formulating mathematical models, performing dimensional analysis, optimizing systems, running simulations, or evaluating model validity.
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。
Systems engineering covering requirements management, the V-model lifecycle, integration planning, verification and validation (V&V), interface control, trade studies, and the NASA Systems Engineering Handbook. Spans the full lifecycle from concept through operations and disposal. Includes requirements decomposition, traceability matrices, configuration management, and technical performance measures. Use when managing complex system development, writing requirements, planning integration, or conducting V&V activities.
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。
Supervised and unsupervised learning, bias-variance tradeoff, cross-validation, decision trees, ensemble methods, neural network fundamentals, and the practitioner's workflow from problem framing through deployment. Covers classification, regression, clustering, dimensionality reduction, regularization, hyperparameter tuning, and evaluation metrics. Use when building predictive models, selecting algorithms, or understanding the machine learning pipeline.
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。
Regression analysis, ANOVA, generalized linear models, Bayesian methods, and model selection. Covers the full modeling workflow from problem formulation through diagnostics -- linear regression, logistic regression, Poisson regression, mixed-effects models, prior specification, posterior inference, AIC/BIC comparison, cross-validation for model selection, and assumption checking. Use when fitting models, testing hypotheses, or selecting among competing statistical explanations.
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。
OpenStack Heat orchestration service skill. Use when working with HOT templates, stack lifecycle management, auto-scaling groups, nested stacks, resource type registry, template validation, or infrastructure-as-code patterns within OpenStack. Covers deployment via Kolla-Ansible, template authoring, stack operations, and troubleshooting common orchestration failures.
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。
Mathematical verification for physical calculations: unit tracking algebra (exponent maps), PhysicalQuantity pattern for compound units, SI/Imperial mixed-unit handling, Buckingham pi theorem for dimensionless groups, and common engineering dimensionless numbers. Activates for unit verification, dimensional consistency checks, scaling analysis, and calculation validation across all infrastructure domains.
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。
Water-based fluid system design: pipe sizing (Darcy-Weisbach, Hazen-Williams), flow rates, pressure drops, CDU selection for DTC cooling, pump curves, and ASHRAE TC 9.9 water class enforcement. Activates for cooling loop design, plumbing calculations, CDU selection, pump sizing, and hydraulic system validation.
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。
Testing and debugging for Zephyr RTOS. Covers the Ztest framework for unit and integration tests, the Twister test runner for automated HIL/SIM validation, and advanced tracing/debugging techniques (SystemView, Thread Analyzer, Stack analysis). Trigger when writing unit tests, setting up CI/CD pipelines, or analyzing system performance and latency.
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 comprehensive clinical reports including case reports (CARE guidelines), diagnostic reports (radiology/pathology/lab), clinical trial reports (ICH-E3, SAE, CSR), and patient documentation (SOAP, H&P, discharge summaries). Full support with templates, regulatory compliance (HIPAA, FDA, ICH-GCP), and validation tools.
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。
MLX↔JAX bidirectional beacon-repeater with spectral gap random walk, justfile orchestration, catp flow validation, and adversarial malleability for life pattern resurrection.
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。
BDD-Driven Mathematical Content Verification Skill Combines Behavior-Driven Development with mathematical formula extraction, verification, and transformation using: - Cucumber/Gherkin for specification - RSpec for implementation verification - mathpix-gem for LaTeX/mathematical content extraction - Pattern matching on syntax trees for formula validation Enables iterative discovery and verification of mathematical properties through executable specifications.
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。