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Found 5,520 Skills
A Pythonic interface to the HDF5 binary data format. It allows you to store huge amounts of numerical data and easily manipulate that data from NumPy. Features a hierarchical structure similar to a file system. Use for storing datasets larger than RAM, organizing complex scientific data hierarchically, storing numerical arrays with high-speed random access, keeping metadata attached to data, sharing data between languages, and reading/writing large datasets in chunks.
This skill should be used when the user asks questions about startups, founding decisions, co-founders, fundraising, product development, growth, hiring, or any entrepreneurial advice. It provides access to Y Combinator's complete library of 443 curated resources including essays by Paul Graham, founder interviews, and startup school lectures. Use this skill to give thorough, research-backed advice on startup decisions.
Use when user describes a complex project goal, wants to set up multiple skills at once, asks "what skills do I need for X", or needs to manage installed skill bundles. Triggers on multi-skill setup, skill combination, project bootstrapping, or batch skill management.
Reviews feature specifications for completeness, testability, and implementation readiness. Validates acceptance criteria, edge cases, and technical constraints. Use when reviewing feature specs before implementation or during sprint planning.
When a user is stuck, frustrated, or describing a problem vaguely, do NOT immediately suggest solutions. First, force structured problem articulation through targeted questions: What did you expect? What happened instead? What have you tried? Only after the problem is clearly defined, propose solutions.
Collaboratively turn ambiguous ideas into implementation-ready designs before coding. Use when requests involve new features, behavior changes, architecture decisions, or prompts like "brainstorm", "design this", "plan this", or "think through options". Clarify intent via one-question-at-a-time dialogue, compare 2-3 approaches with trade-offs, and converge on a validated design spec.
Comprehensive expertise in decentralized prediction markets, including Polymarket-style platforms, UMA Optimistic Oracle integration, Conditional Tokens Framework (CTF), market making, resolution mechanisms, and regulatory considerations. Use when "prediction market, Polymarket, betting market, outcome tokens, resolution oracle, UMA oracle, conditional tokens, binary market, outcome prediction, information market, " mentioned.
CQRS (Command Query Responsibility Segregation) patterns for separating read and write models. Use when optimizing read-heavy systems, implementing event sourcing, or building systems with different read/write scaling requirements.
Production hybrid search combining PGVector HNSW with BM25 using Reciprocal Rank Fusion. Use when implementing hybrid search, semantic + keyword retrieval, vector search optimization, metadata filtering, or choosing between HNSW and IVFFlat indexes.
Implement Customer Portal for subscription self-service. Use when building account pages, letting customers manage subscriptions, update payment methods, view billing history, or when user mentions "customer portal", "帳戶管理", "訂閱管理", "更新付款方式", "self-service".
Use when modern C++ features from C++11/14/17/20 including auto, lambdas, range-based loops, structured bindings, and concepts.
合并多个视频文件为一个视频。Use when user wants to 合并视频, 拼接视频, 视频合并, 视频拼接, 把视频合在一起, 连接视频, join videos, merge videos, combine videos, concatenate videos.