向量嵌入
向量检索与嵌入工作流
AgentDB Memory Patterns
ruvnet
"Implement persistent memory patterns for AI agents using AgentDB. Includes session memory, long-term storage, pattern learning, and context management. Use when building stateful agents, chat systems, or intelligent assistants."
esm
K-Dense-AI
Comprehensive toolkit for protein language models including ESM3 (generative multimodal protein design across sequence, structure, and function) and ESM C (efficient protein embeddings and representations). Use this skill when working with protein sequences, structures, or function prediction; designing novel proteins; generating protein embeddings; performing inverse folding; or conducting protein engineering tasks. Supports both local model usage and cloud-based Forge API for scalable inference.
clip
majiayu000
OpenAI's model connecting vision and language. Enables zero-shot image classification, image-text matching, and cross-modal retrieval. Trained on 400M image-text pairs. Use for image search, content moderation, or vision-language tasks without fine-tuning. Best for general-purpose image understanding.
Scout — Skill Discovery & Installation
anton-abyzov
"START HERE — Skill discovery and installation assistant. The recommended first skill when you don't know which skills you need. Searches verified-skill.com, recommends plugin bundles, and installs skills. Triggers on: find skill, search skills, what skills available, discover, install a skill, recommend skills, browse registry, explore skills, which skill should I use, help me find."
theming-tokens
fusengine
Use when creating theme systems, color variables, or design system tokens. Covers primitives, semantic, and component tokens.
chroma
majiayu000
Open-source embedding database for AI applications. Store embeddings and metadata, perform vector and full-text search, filter by metadata. Simple 4-function API. Scales from notebooks to production clusters. Use for semantic search, RAG applications, or document retrieval. Best for local development and open-source projects.
faiss
majiayu000
Facebook's library for efficient similarity search and clustering of dense vectors. Supports billions of vectors, GPU acceleration, and various index types (Flat, IVF, HNSW). Use for fast k-NN search, large-scale vector retrieval, or when you need pure similarity search without metadata. Best for high-performance applications.
bioservices
K-Dense-AI
Unified Python interface to 40+ bioinformatics services. Use when querying multiple databases (UniProt, KEGG, ChEMBL, Reactome) in a single workflow with consistent API. Best for cross-database analysis, ID mapping across services. For quick single-database lookups use gget; for sequence/file manipulation use biopython.
chembl-database
K-Dense-AI
Query ChEMBL bioactive molecules and drug discovery data. Search compounds by structure/properties, retrieve bioactivity data (IC50, Ki), find inhibitors, perform SAR studies, for medicinal chemistry.
bindingdb-database
K-Dense-AI
Query BindingDB for measured drug-target binding affinities (Ki, Kd, IC50, EC50). Search by target (UniProt ID), compound (SMILES/name), or pathogen. Essential for drug discovery, lead optimization, polypharmacology analysis, and structure-activity relationship (SAR) studies.
ads-budget
AgriciDaniel
Budget allocation and bidding strategy review across all ad platforms. Evaluates spend distribution, bidding strategy appropriateness, scaling readiness, and identifies campaigns to kill or scale. Uses 70/20/10 rule, 3x Kill Rule, and 20% scaling rule. Use when user says "budget allocation", "bidding strategy", "ad spend", "ROAS target", "media budget", or "scaling".
agent-reach
Panniantong
Use the internet: search, read, and interact with 13+ platforms including Twitter/X, Reddit, YouTube, GitHub, Bilibili, XiaoHongShu (小红书), Douyin (抖音), WeChat Articles (微信公众号), LinkedIn, Boss直聘, RSS, Exa web search, and any web page. Use when: (1) user asks to search or read any of these platforms, (2) user shares a URL from any supported platform, (3) user asks to search the web, find information online, or research a topic, (4) user asks to post, comment, or interact on supported platforms, (5) user asks to configure or set up a platform channel. Triggers: "搜推特", "搜小红书", "看视频", "搜一下", "上网搜", "帮我查", "全网搜索", "search twitter", "read tweet", "youtube transcript", "search reddit", "read this link", "看这个链接", "B站", "bilibili", "抖音视频", "微信文章", "公众号", "LinkedIn", "GitHub issue", "RSS", "search online", "web search", "find information", "research", "帮我配", "configure twitter", "configure proxy", "帮我安装".
wiki-retrieve
AgriciDaniel
"Build and query a vault-local contextual BM25 retrieval index with optional multilingual Nomic cosine reranking; use for retrieve, hybrid retrieval, BM25, rerank, contextual retrieval, chunk search, vault search, semantic search, find relevant passages, or retrieval diagnostics. Derived caches stay under .vault-meta, remote egress requires explicit consent, and unavailable reranking falls back deterministically."
Obsidian Vault
mattpocock
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ads-google
AgriciDaniel
Google Ads deep analysis covering Search, Performance Max, Display, YouTube, and Demand Gen campaigns. Evaluates 74 checks across conversion tracking, wasted spend, account structure, keywords, ads, and settings. Use when user says "Google Ads", "Google PPC", "search ads", "PMax", "Performance Max", or "Google campaign".
ai-engineer
benjaminasterA
"Build production-ready LLM applications, advanced RAG systems, and"
agent-memory-systems
benjaminasterA
"Memory is the cornerstone of intelligent agents. Without it, every interaction starts from zero. This skill covers the architecture of agent memory: short-term (context window), long-term (vector s..."
xint
0xNyk
X Intelligence CLI — search, analyze, and engage on X/Twitter from the terminal. Use when: (1) user says "x research", "search x for", "search twitter for", "what are people saying about", "what's twitter saying", "check x for", "x search", "search x", "find tweets about", "monitor x for", "track followers", (2) user is working on something where recent X discourse would provide useful context (new library releases, API changes, product launches, cultural events, industry drama), (3) user wants to find what devs/experts/community thinks about a topic, (4) user needs real-time monitoring ("watch"), (5) user wants AI-powered analysis ("analyze", "sentiment", "report"). Also supports: bookmarks, likes, following (read/write), trending topics, Grok AI analysis, and cost tracking. Export as JSON, JSONL (pipeable), CSV, or Markdown. Non-goals: Not for posting tweets, not for DMs, not for enterprise features. Requires OAuth for user-context operations (bookmarks, likes, following, diff).
/search-first — Research Before You Code
affaan-m
Research-before-coding workflow. Search for existing tools, libraries, and patterns before writing custom code. Invokes the researcher agent.
senior-prompt-engineer
borghei
Expert prompt engineering for LLM applications including prompt design, optimization, RAG systems, agent architectures, and AI product development.
postgresql-table-design
wshobson
Design a PostgreSQL-specific schema. Covers best-practices, data types, indexing, constraints, performance patterns, and advanced features
lookalike-customer-finder
OneWave-AI
Input your best customers and find 100+ companies that match the profile. Uses firmographic data, tech stack, growth signals, and similarity scoring to identify ideal prospects. Use when building target account lists or expanding to new markets.
google-ads
kostja94
When the user wants to set up, optimize, or manage Google Ads campaigns. Also use when the user mentions "Google Ads," "Google Search Ads," "PPC," "SEM," "PMF testing with ads," "test product-market fit," "Responsive Search Ads," "RSA," "Performance Max," "Quality Score," "keyword bidding," or "Google Display/YouTube ads."
app-ads
kostja94
When the user wants to run app install ads, user acquisition (UA), or promote mobile apps. Also use when the user mentions "app ads," "app install ads," "UA," "user acquisition," "Google App Campaigns," "Apple Search Ads," "ASA," "UAC," "App Store ads," "Play Store ads," "CPI," or "app promotion."