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Found 736 Skills
Creates comprehensive permission tests ensuring RBAC doesn't regress with test matrices, CI gating, and authorization coverage. Use for "RBAC testing", "permission tests", "authorization testing", or "access control tests".
Application monitoring and observability setup for Python/React projects. Use when configuring logging, metrics collection, health checks, alerting rules, or dashboard creation. Covers structured logging with structlog, Prometheus metrics for FastAPI, health check endpoints, alert threshold design, Grafana dashboard patterns, error tracking with Sentry, and uptime monitoring. Does NOT cover incident response procedures (use incident-response) or deployment (use deployment-pipeline).
Given a domain, identify the few independent forces that truly underpin it. Reduce dozens of phenomena to the minimal set of generators—only when you can regenerate all phenomena from these generators does it count. Use this when the user says 'rank reduction', 'find rank', 'what is rank', 'what supports this domain', 'what lies behind it', or wants to decompose any domain into its irreducible generators.
Review local git changes and perform a light code review. If no issues are found, commit the changes. Does NOT write or modify code — only reviews and commits. Optionally accepts a commit message header as an argument.
Generate read-only MongoDB queries (find) or aggregation pipelines using natural language, with collection schema context and sample documents. Use this skill whenever the user asks to write, create, or generate MongoDB queries, wants to filter/query/aggregate data in MongoDB, asks "how do I query...", needs help with query syntax, or discusses finding/filtering/grouping MongoDB documents. Also use for translating SQL-like requests to MongoDB syntax. Does NOT handle Atlas Search ($search operator), vector/semantic search ($vectorSearch operator), fuzzy matching, autocomplete indexes, or relevance scoring - use search-and-ai for those. Does NOT analyze or optimize existing queries - use mongodb-query-optimizer for that. Does NOT handle aggregation pipelines that involve write operations. Requires MongoDB MCP server.
Guides Qdrant scaling decisions. Use when someone asks 'how many nodes do I need', 'data doesn't fit on one node', 'need more throughput', 'cluster is slow', 'too many tenants', 'vertical or horizontal', 'how to shard', or 'need to add capacity'.
Diagnoses .NET Framework CLR activation issues using CLR activation logs (CLRLoad logs) produced by mscoree.dll. Use when: the shim picks the wrong runtime, fails to load any runtime, shows unexpected .NET 3.5 Feature-on-Demand (FOD) dialogs, unexpectedly does NOT show FOD dialogs, loads both v2 and v4 into the same process causing failures, or any time someone is wondering "what is happening with .NET Framework activation?"
Build a complete brand identity and guidelines PDF from any input — an idea, an existing website, a list of reference brands, product photos, or "I want to rebrand X". Use when someone wants a brand identity but does NOT need a full commerce launch (no Shopify, no product listings, no social posting). Trigger phrases: "build me a brand", "make me a brand", "design a brand identity", "brand guidelines for [X]", "i want a brand book", "create a brand from scratch", "brand for [idea]", "i want a brand that feels like [X] + [Y]", "rebrand my [thing]", "visual identity for [thing]", "build-a-brand".
Map of every agentmemory MCP tool, what each does, and its parameters. Use when choosing which memory tool to call, when a tool name or argument is unclear, or when answering what agentmemory can do via MCP.
Use when learning Rust concepts. Keywords: mental model, how to think about ownership, understanding borrow checker, visualizing memory layout, analogy, misconception, explaining ownership, why does Rust, help me understand, confused about, learning Rust, explain like I'm, ELI5, intuition for, coming from Java, coming from Python, 心智模型, 如何理解所有权, 学习 Rust, Rust 入门, 为什么 Rust
Clear description of what this skill does and when to use it
Deep contextual grep for codebases. Expert at finding patterns, architectures, implementations, and answering "Where is X?", "Which file has Y?", and "Find code that does Z" questions. Use when exploring unfamiliar codebases, finding specific implementations, understanding code organization, discovering patterns across multiple files, or locating functionality in a project. Supports three thoroughness levels quick, medium, very thorough.