Loading...
Loading...
Found 1,575 Skills
Diseño de prompts para LLMs: system prompts, few-shot examples, chain-of-thought, RAG, structured outputs.
ConvexFS (convex-fs) — path-based file storage and serving component for Convex powered by bunny.net CDN. Covers installation, setup, file upload/download flows, path management, blob lifecycle, atomic transactions (move/copy/delete), compare-and-swap, signed URLs, file expiration, garbage collection, auth for uploads/downloads, multiple filesystems, React integration, and production best practices. Use when working with ConvexFS, uploading files in Convex, serving files via CDN, managing file paths, building file storage features, or configuring bunny.net with Convex. Triggers on: convex-fs, ConvexFS, bunny.net, file upload, file storage convex, blob, commitFiles, registerRoutes, buildDownloadUrl, fs.stat, fs.list, fs.transact, fs.move, fs.copy, fs.delete, fs.writeFile, fs.getDownloadUrl, "how do I upload files in Convex", "serve files from Convex", "ConvexFS setup".
Use OpenSearch vector search edition via the Python SDK (ha3engine) to push documents and run HA/SQL searches. Ideal for RAG and vector retrieval pipelines in Claude Code/Codex.
AI and machine learning workflow covering LLM application development, RAG implementation, agent architecture, ML pipelines, and AI-powered features.
Document undocumented public APIs in PyTorch by removing functions from coverage_ignore_functions and coverage_ignore_classes in docs/source/conf.py, running Sphinx coverage, and adding the appropriate autodoc directives to the correct .md or .rst doc files. Use when a user asks to remove functions from conf.py ignore lists.
Betting analysis — odds conversion, de-vigging, edge detection, Kelly criterion, arbitrage detection, parlay analysis, and line movement. Pure computation, no API calls. Works with odds from any source: ESPN (American odds), Polymarket (decimal probabilities), Kalshi (integer probabilities). Use when: user asks about bet sizing, expected value, edge analysis, Kelly criterion, arbitrage, parlays, line movement, odds conversion, or comparing odds across sources. Also use when you have odds from ESPN and a prediction market price and want to evaluate whether a bet has positive expected value. Don't use when: user asks for live odds or market data — use polymarket, kalshi, or the sport-specific skill to fetch odds first, then use this skill to analyze them.
Supermemory is a state-of-the-art memory and context infrastructure for AI agents. Use this skill when building applications that need persistent memory, user personalization, long-term context retention, or semantic search across knowledge bases. It provides Memory API for learned user context, User Profiles for static/dynamic facts, and RAG for semantic search. Perfect for chatbots, assistants, and knowledge-intensive applications.
Use when you need legal PDF to markdown extraction plus clause chunking and embedding prep; pair with addon-rag-ingestion-pipeline and architect-python-uv-batch.
Generates secure Aptos Move V2 smart contracts with Object model, Digital Asset integration, security patterns, and storage type guidance. Includes comprehensive storage decision framework for optimal data structure selection. Triggers on: 'write contract', 'create NFT collection', 'build marketplace', 'implement minting', 'generate Move module', 'create token contract', 'build DAO', 'implement staking'. Ask storage questions when: 'store', 'track', 'registry', 'mapping', 'list', 'collection'.
Creates comprehensive test suites for Move contracts with 100% coverage requirement. Triggers on: 'generate tests', 'create tests', 'write test suite', 'test this contract', 'how to test', 'add test coverage', 'write unit tests'.
Guide for conducting thorough and synthesized research, focusing on verification, multi-source analysis, and RAG patterns.
Extract structured data from Office documents (DOCX, PPTX, XLSX, HWP, HWPX) using the Polaris AI DataInsight Doc Extract API. Use when the user wants to parse, analyze, or extract text, tables, charts, images, or shapes from document files. Invoke this skill whenever the user mentions extracting content from Word, PowerPoint, Excel, HWP, or HWPX files, wants to parse document structure, needs to convert document data for RAG pipelines, or asks about reading tables, charts, or text from Office-format documents — even if they don't explicitly mention "DataInsight" or "Polaris".