Expert patterns for Azure Functions development including isolated worker model, Durable Functions orchestration, cold start optimization, and production patterns. Covers .NET, Python, and Node.js programming models.
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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Expert patterns for Azure Functions development including isolated worker model, Durable Functions orchestration, cold start optimization, and production patterns. Covers .NET, Python, and Node.js programming models.
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。
Analyze market conditions, geographic opportunities, pricing, consumer behavior, and product validation across Google Maps, Facebook, Instagram, Booking.com, and TripAdvisor.
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 assessing AI/ML systems for prompt injection, jailbreak vulnerabilities, model inversion risk, data poisoning exposure, or agent tool abuse. Covers MITRE ATLAS technique mapping, injection signature detection, and adversarial robustness scoring.
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。
Inter-agent communication protocol for C-suite agent teams. Defines invocation syntax, loop prevention, isolation rules, and response formats. Use when C-suite agents need to query each other, coordinate cross-functional analysis, or run board meetings with multiple agent roles.
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 collaboration plugin that spawns N parallel subagents competing on the same task via git worktree isolation. Agents work independently, results are evaluated by metric or LLM judge, and the best branch is merged. Use when: user wants multiple approaches tried in parallel — code optimization, content variation, research exploration, or any task that benefits from parallel competition. Requires: a git repo.
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。
/cs:aims-audit <scope> — ISO/IEC 42001 AIMS internal-audit 6-question forcing interrogation. Use before certification stage 1, before annual internal audit cycles, or when onboarding a new AI system into an existing AIMS.
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 asks to design a multi-agent system, pick an orchestration pattern (supervisor/swarm/pipeline), generate tool schemas for agents, or evaluate agent execution logs for cost, latency, and failure bottlenecks. Examples: 'design an agent architecture for research automation', 'generate Anthropic tool schemas from these tool descriptions', 'analyze these agent run logs for bottlenecks'. NOT for Claude Code workflow files (use workflow-builder) or single-agent prompt design (use agent-workflow-designer).
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。
Autonomous DevSecOps & FinOps Guardrails. Orchestrates Gemini 3 Flash to audit Linux Kernel patches, Terraform cost drifts, and K8s compliance.
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。
This skill should be used when the user asks to "implement LLM-as-judge", "compare model outputs", "create evaluation rubrics", "mitigate evaluation bias", or mentions direct scoring, pairwise comparison, position bias, evaluation pipelines, or automated quality assessment.
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, reviewing, refactoring, or enforcing Angular application architecture with isolated lazy features, eager core/layout, reusable ui/pattern architecture building blocks, one-way dependency graphs, eslint-plugin-boundaries rules, or folder placement decisions. This skill takes precedence over angular-developer when architecture rules conflict with general Angular advice.
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。
Capture baseline evidence from a live website URL: screenshots, scroll states, hover/click behavior, parallax, timers, and transition recordings. Use when reference artifacts are needed before implementation or comparison; not to build or diagnose a clone.
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 whether tests detect broken behavior by tracing assertions and running narrow controlled mutations in an isolated workspace; use for test-quality reviews, not routine test execution.
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。
Discover B2B leads from Reddit using AI-powered lead scoring via reddapi.dev Leads API. Finds high-intent signals, scores them 0-100, and classifies by lead type (pain_point, solution_request, complaint, feature_request, comparison). Perfect for competitor poaching, pain point discovery, and sales prospecting.
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。
Standalone browser-based visual companion for interactive mockups, diagrams, wireframes, layout comparisons, visual brainstorming, and clickable visual option 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。
Use when a user wants a standalone browser-based visual companion for interactive mockups, diagrams, wireframes, layout comparisons, visual brainstorming, or clickable visual option selection. Starts a local zero-dependency Node server, writes HTML screens, and reads browser click events.
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 leakage-safe machine learning experiments that mirror real deployment and support fair model comparisons. Use when defining prediction timing, feature eligibility, train-validation-test splits, baselines, metrics, or controlled model iterations; not for auditing whether raw labels are trustworthy.
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 an end-to-end data analysis or machine learning project from decision framing through reproducible handoff. Use when a request spans multiple lifecycle stages or an ambiguous modeling request must become a decision-ready result; use narrower audit or experiment-design skills for isolated reviews.
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。
Isolate the root cause of ML performance drops, inconsistent evaluations, prediction errors, and training-serving mismatches across data, labels, splits, pipelines, models, metrics, and runtime behavior. Use when investigating a reproducible failure or regression, not routine model selection or general performance 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。
Resolve repository documentation authority, repair reading paths and explanations, or shape a bounded public projection. Maintain docs after a bounded change when indirect reader promises, generated or paired sources, version/evidence boundaries, or unclear authority need attention. Ordinary known updates stay in normal development; not for isolated prose polishing, code review, or broad runtime audits.
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。
Investigate two separate areas of the codebase simultaneously and combine findings into a comparison report. Use when you need research on two independent topics at once, want to compare two subsystems, or need to understand how two components relate to each other.
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 npm or pip dependencies for outdated packages and known vulnerabilities. Use when checking package health, preparing for a release, reviewing dependencies before merging a PR, or when asked about outdated packages or security advisories.
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-level medical device design covering regulatory pathways, design controls, biocompatibility, sterilization, risk management, and verification and 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。
Expert-level biomaterials covering biocompatibility, metals, ceramics, and polymers for medical implants, surface modification, host response, and regulatory considerations.
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-level medicinal chemistry knowledge. Use when working with drug design, structure-activity relationships, ADMET properties, pharmacophores, lead optimization, target identification, drug metabolism, or pharmaceutical development. Also use when the user mentions 'SAR', 'drug design', 'pharmacophore', 'ADMET', 'lead compound', 'hit to lead', 'drug metabolism', 'bioavailability', 'selectivity', 'binding affinity', 'scaffold hopping', or 'bioisostere'.
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。