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Found 5,586 Skills
Template-based AI prompt engine with YAML templates, brand kit injection, input sanitization for security, and token-efficient context blocks.
Use when extracting entities and relationships, building ontologies, compressing large graphs, or analyzing knowledge structures - provides structural equivalence-based compression achieving 57-95% size reduction, k-bisimulation summarization, categorical quotient constructions, and metagraph hierarchical modeling with scale-invariant properties. Supports recursive refinement through graph topology metrics including |R|/|E| ratios and automorphism analysis.
Transform structured external data (CSV/JSON) into Obsidian's linked knowledge system while preserving semantic relationships, optimizing graph structure, and preventing data corruption through systematic validation and YAML-safe template generation.Enables seamless knowledge transfer from databases, spreadsheets, and APIs into personal knowledge management, maintaining referential integrity and facilitating emergence of insights through networked thought.
Expert guidance for building production-ready FastAPI applications with modular architecture where each business domain is an independent module with own routes, models, schemas, services, cache, and migrations. Uses UV + pyproject.toml for modern Python dependency management, project name subdirectory for clean workspace organization, structlog (JSON+colored logging), pydantic-settings configuration, auto-discovery module loader, async SQLAlchemy with PostgreSQL, per-module Alembic migrations, Redis/memory cache with module-specific namespaces, central httpx client, OpenTelemetry/Prometheus observability, conversation ID tracking (X-Conversation-ID header+cookie), conditional Keycloak/app-based RBAC authentication, DDD/clean code principles, and automation scripts for rapid module development. Use when user requests FastAPI project setup, modular architecture, independent module development, microservice architecture, async database operations, caching strategies, logging patterns, configuration management, authentication systems, observability implementation, or enterprise Python web services. Supports max 3-4 route nesting depth, cache invalidation patterns, inter-module communication via service layer, and comprehensive error handling workflows.
Automatically detect and suggest appropriate MCP tools (context7, grep_app, web_search) based on user queries. This applies when queries contain documentation keywords (including English terms like how to use, docs, API, guide, tutorial and Chinese terms like 如何使用, 文档, 教程); code search keywords (including English terms like example, implementation, source code, github and Chinese terms like 例子, 示例, 实现, 源码); or latest information/bug fixing keywords (including English terms like latest, 2025, 2026, new, update, fix bug, error and Chinese terms like 最新, 更新, 修复 bug, 报错).
Enterprise React architecture combining DDD and FSD patterns. Use when (1) designing or structuring React applications, (2) implementing Index/Types/Styles component pattern, (3) setting up Service/Hook 1:1 mapping with React Query and Axios, (4) configuring Zustand state management, (5) applying TypeScript conventions for maintainable codebases. Triggers include architectural decisions, folder structure planning, data layer design, and code organization tasks.
Advanced TMF628 analytics skill. Handles time-series filtering, threshold extraction, and severity-based ranking for network hotspots.
Run OWASP ZAP for Dynamic Application Security Testing. Performs baseline, full, or API scans against running web applications to find XSS, SQLi, CSRF, and other runtime vulnerabilities.
Decision-making framework for software development, Y Combinator / Silicon Valley style. Based on real principles from Paul Graham, Sam Altman, Michael Seibel, Patrick Collison, and Brian Chesky. Use when: - Developing features or products - Making technical decisions (what to do, how, when) - Prioritizing work (P0, P1, P2) - Evaluating whether to refactor or patch - Deciding on technical debt - Evaluating whether to add tests, CI/CD, or automation - Any architecture or engineering decision Triggers: development, code, feature, refactor, architecture, prioritize, technical decision, what to do first, technical debt, tests, CI/CD, sprint, backlog
Run Anchore Grype for SCA vulnerability scanning on filesystems and container images. Matches dependencies against multiple vulnerability databases (NVD, GitHub, OS advisories).
Exclusive skill set for the GoFrame development framework. Provides a complete framework usage guide for Go language developers, covering best practices for core components such as command-line management, configuration management, logging components, error handling, data validation, type conversion, cache management, template engines, database ORM, and I18n internationalization. Includes project engineering structure specifications, development model guidelines, solutions to common problems, and rich practical code examples. Suitable for building various Go projects such as RESTful APIs, gRPC microservices, and web applications, helping developers quickly master the features of the GoFrame framework and improve development efficiency and code quality.
Generates complete starter repositories for various tech stacks (Next.js, Vite, Nest, FastAPI, etc.) with best-practice conventions, folder structure, baseline code, configs, scripts, and setup documentation. Use when users request to "scaffold a project", "create a starter repo", "initialize a new project", or specify a tech stack to begin with.