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Design and build production-ready frontend interfaces with design systems, responsive layouts, accessible components, and dark mode support. Use when the user requests frontend design or provides relevant inputs for this workflow.

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 professional, scalable logos with complete brand identity deliverables including color palettes, typography, format variations, and usage guidelines. Use when the user requests logo design or provides relevant inputs for this workflow.

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 open-source license compatibility, obligations, and compliance risks across project dependencies. Use when the user requests license analysis or provides relevant inputs for this workflow.

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。

Classify expenses by category, department, and tax deductibility from transaction data. Use when the user requests expense categorization or provides relevant inputs for this workflow.

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。

Scan project dependencies for known vulnerabilities, generate software bills of materials, and enforce license compliance across the software supply chain. Use when the user requests dependency scanning or provides relevant inputs for this workflow.

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。

Compress selected context to a target token budget while preserving decisions, evidence, constraints, and unresolved questions. Use when relevant material is already selected but too long; use context-optimization when selection, deduplication, and ordering are also 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。

Plan, execute, document, and retest authorized security assessments of AI agents and multi-agent workflows using safe adversarial cases, synthetic identities, canaries, and evidence-based findings. Use when defining red-team rules of engagement, assessing prompt injection or excessive agency, testing tool and identity boundaries, evaluating memory or cross-agent attacks, scoring a campaign, or verifying remediation in an approved environment.

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。

Threat-model and harden AI agents, RAG systems, assistants, and tool-using workflows against direct, indirect, stored, cross-agent, and multimodal prompt injection. Use when reviewing an agent architecture, isolating untrusted content, constraining tools and egress, protecting secrets, adding injection-focused tests, investigating a suspected injection incident, or documenting residual prompt-injection risk.

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 agent skills, plugins, prompts, manifests, scripts, dependencies, and bundled assets for provenance, prompt-injection, permission, execution, exfiltration, persistence, and update risk. Use when evaluating a third-party skill before installing, enabling, updating, publishing, or distributing it; reviewing an untrusted SKILL.md, agent configuration, MCP integration, archive, or repository; comparing a package with a known-good version; or investigating unexpected tool, network, credential, or filesystem behavior.

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 manage data labeling workflows using manual annotation tools, semi-automated pipelines, active learning, and programmatic weak supervision. Use when the user requests data labeling or provides relevant inputs for this workflow.

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, implement, and validate reproducible machine-learning pipelines spanning data preparation, training, evaluation, registry, and deployment gates. Use when the user requests an ML pipeline, needs to turn model scripts into an orchestrated workflow, or provides pipeline components that must be connected safely.

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 trained machine learning models as production-ready services using REST APIs, containers, serverless functions, and orchestration platforms. Use when the user requests model deployment or provides relevant inputs for this workflow.

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 RESTful APIs with proper resource modeling, HTTP method semantics, status codes, pagination, versioning, and documentation. Use when the user requests api design or provides relevant inputs for this workflow.

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 with external APIs using REST clients, webhook consumers, SDK wrappers, and polling patterns with proper authentication, error handling, and retry logic. Use when the user requests api integration or provides relevant inputs for this workflow.

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 GraphQL APIs with well-structured schemas, efficient resolvers, pagination, and performance patterns like DataLoader and federation. Use when the user requests graphql api design or provides relevant inputs for this workflow.

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 OAuth 2.0 authentication flows including authorization code with PKCE, client credentials, and device code for secure API integration. Use when the user requests oauth 2 0 setup or provides relevant inputs for this workflow.

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。

Automatically generate clear, comprehensive documentation for codebases — including API references, inline docstrings, README files, and usage guides. Use when the user requests code documentation or provides relevant inputs for this workflow.

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。

Perform thorough code reviews on files or pull requests, checking for bugs, security vulnerabilities, performance issues, and style violations. Use when the user requests code review or provides relevant inputs for this workflow.

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。

Draft a professional, audience-aware email or reply with calibrated tone and a clear call to action. Use when the user needs one message, response, follow-up, support note, or meeting request; use sales-email-sequences for a coordinated multi-touch outbound campaign.

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。

Optimize a complete candidate context package by deduplicating, filtering, ordering, and allocating its token budget. Use when retrieved or assembled material is noisy or exceeds the useful context budget; use context-ranking for scoring chunks and context-compression for shrinking selected content.

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。

Rank an existing set of context chunks by relevance, diversity, freshness, and utility. Use when retrieval has already produced candidates that must be scored or reranked; use context-retrieval when the source corpus still needs to be searched.

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。

Identify at-risk customer accounts by analyzing usage patterns, engagement signals, and support history to generate churn risk scores and intervention recommendations. Use when the user requests churn analysis or provides relevant inputs for this workflow.

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 NPS, CSAT, and qualitative customer feedback to extract themes, identify trends, and generate actionable insight reports. Use when the user requests customer feedback analysis or provides relevant inputs for this workflow.

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 clear, searchable help center articles and FAQ entries based on support data, product documentation, and common customer questions. Use when the user requests knowledge base article writing or provides relevant inputs for this workflow.

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。