4.7K skills · sorted by relevance
Azure Cosmos DB SDK for Python (NoSQL API). Use for document CRUD, queries, containers, and globally distributed data.
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Azure Event Grid SDK for Python. Use for publishing events, handling CloudEvents, and event-driven architectures.
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Azure App Configuration SDK for Python. Use for centralized configuration management, feature flags, and dynamic settings.
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Azure Identity SDK for Python authentication. Use for DefaultAzureCredential, managed identity, service principals, and token caching.
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Azure Tables SDK for Python (Storage and Cosmos DB). Use for NoSQL key-value storage, entity CRUD, and batch operations.
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Azure Machine Learning SDK v2 for Python. Use for ML workspaces, jobs, models, datasets, compute, and pipelines.
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Astropy is the core Python package for astronomy, providing essential functionality for astronomical research and data analysis.
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Azure AI Content Safety SDK for Python. Use for detecting harmful content in text and images with multi-severity classification.
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Azure AI Content Understanding SDK for Python. Use for multimodal content extraction from documents, images, audio, and video.
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Answer Engine Optimization (AEO) skill — optimize content to be cited by AI language models (ChatGPT, Perplexity, Claude, Gemini, Mistral) as authoritative sources. Distinct from SEO — AEO optimizes for citation in LLM-generated responses, not search rankings. Use when planning content for AI-first search audiences, auditing existing content for E-E-A-T signals, tracking which pages get cited by which LLMs, or building a citation-friendly content strategy. Triggers — 'AEO audit', 'optimize for ChatGPT', 'get cited by Perplexity', 'LLM citation strategy', 'answer engine optimization', 'content for AI search', 'E-E-A-T audit'. Output is a markdown audit report (default) or JSON for pipeline integration. Stdlib-only Python tools.
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Build persistent agents on Azure AI Foundry using the Microsoft Agent Framework Python SDK.
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为一个项目端到端生成一整套风格统一的图标：读代码梳理图标清单、定风格锚点、4×4网格默认批量生成（16个一张，精度不够时逐个兜底重生）、智能抠图、落位到项目正确路径并更新代码引用、输出交付报告。当用户说「给项目配一套图标」「生成图标集」「统一项目图标风格」「替换项目里的图标」「批量画图标」，或项目中存在图标资源目录、需要批量新增或替换图标时使用。依赖豆包内置生图能力（image_gen / image_edit 的 image_reference_url_list 参考图机制）和本地 Python+Pillow+numpy 抠图环境，离开豆包生图环境无法运行。
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Expert-level bioinformatics covering sequence analysis, structural bioinformatics, database searching, phylogenetic analysis, NGS data processing, single-cell analysis, and machine learning in biology.
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Use when raising code quality or test coverage across a .NET, Java, or Python repository.
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Use when building a new MCP server in TypeScript, Python, or C# that exposes tools to LLMs.
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Guides AI agents through Senzing entity resolution workflows using the Senzing MCP server. Covers data mapping to Senzing format, SDK code generation (Python, Java, C#, Rust, TypeScript/Node.js), documentation search, error troubleshooting, sample data access, reporting and visualization, SDK setup guides, and V3-to-V4 migration. Use when working with entity resolution, record matching, record linkage, deduplication, Senzing SDK integration, data mapping for Senzing ingestion, or troubleshooting Senzing error codes. Also use when the user mentions matching records across data sources, finding duplicate entities, identity resolution, master data management, or needs to resolve who is who across datasets.
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Report the current development environment: Node, Python, OS, git state. Use when debugging environment issues, onboarding, or checking system compatibility.
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Use when building an MCP server in Python (FastMCP) or Node/TypeScript (MCP SDK) — agent-centric tool design, input schemas, error handling, and the 10-question evaluation harness.
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When working within any module under `modules.root_paths` from `.agent-project-settings.yml` — Laravel HMVC, Symfony DDD-lite, Node monorepo, Python src/, Go internal/, or a custom path.
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Use when creating a Laravel/PHP DTO with the SimpleDto base class and attribute mapping. For DTOs in other stacks, use the stack-native skill (TypeScript, Python, Rust, Go).
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Use when invoked as $new-project or when creating a brand-new repository or project from scratch — scaffolds mise-pinned tools, a just task surface, the standard repo files, and CI for Python (uv), TypeScript (bun), Rust (cargo), or Go.
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Adaption AI SDK for synthetic data augmentation and dataset adaptation. Use when building data pipelines with the Adaption Python SDK, uploading datasets (local files, Hugging Face, Kaggle), running augmentation/adaptation jobs, configuring brand controls (hallucination mitigation, safety categories, length), recipe specifications (reasoning traces, deduplication, preference pairs, prompt rephrase), evaluating dataset quality, downloading results, or any workflow involving `pip install adaption`, `from adaption import Adaption`, Adaptive Data, or the adaptionlabs.ai API. Also trigger when the user mentions synthetic data generation for fine-tuning, dataset augmentation pipelines, DPO preference pair generation, or grounding-based hallucination reduction on training data.
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Domain-Driven Design system for software development. Use when designing new systems with DDD principles, refactoring existing codebases toward DDD, generating code scaffolding (entities, aggregates, repositories, domain events), facilitating Event Storming sessions, creating bounded context maps, or performing code reviews with a DDD lens. Covers both strategic design (bounded contexts, subdomains, context maps, ubiquitous language) and tactical design (entities, value objects, aggregates, domain services, repositories). Supports all major architecture patterns (Hexagonal/Ports & Adapters, CQRS, Event Sourcing, Clean Architecture) with language-agnostic guidance and concrete examples in Python and TypeScript.
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Practical security review and hardening guidance for application code in Python, JavaScript/TypeScript, and Go. Use this skill whenever the user asks for a security review or audit, wants to harden authentication (password hashing, sessions, JWT, OAuth2/OIDC, MFA), fix OWASP Top 10 issues (injection, XSS, IDOR, CSRF, SSRF, deserialization), threat-model with STRIDE, clean up secrets and .env handling, or set up dependency scanning (pip-audit, npm audit, osv-scanner, gitleaks, SBOM). Also trigger for "make this secure", "is this safe to deploy", bcrypt/argon2id, rate limiting logins, RBAC/ABAC, CSP and security headers, cookie flags, and secure-by-default coding help.
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