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Found 1,637 Skills
Identify sector rotation, capital switching and style migration directions, help judge the current market main line, compensatory growth directions and rotation sustainability. Suitable for market style observation, sector comparison, post-market review and next-stage main line judgment.
Embed hierarchical data in hyperbolic space via npx ruvector Poincare ball model, compute geodesic distances
Generate embeddings via npx ruvector (ONNX all-MiniLM-L6-v2, 384-dim), normalize, and store in HNSW index
Connect OpenClaw AI agents to DingTalk with message handling, document operations, calendar, todos, and AI cards
Create comprehensive industry and sector landscape reports covering market dynamics, competitive positioning, key players, and thematic trends. Use for client requests, sector initiations, thematic research pieces, or internal knowledge building. Triggers on "sector overview", "industry report", "market landscape", "sector analysis", "industry deep dive", or "thematic research".
Redis vector search guidance covering HNSW vs FLAT algorithm choice, vector index configuration (dims, distance metric, datatype), filtered hybrid search combining vector similarity with TAG or NUMERIC filters, and the RAG retrieval pattern with RedisVL. Use when defining a VECTOR field in FT.CREATE, integrating embeddings (OpenAI, Cohere, sentence-transformers), tuning HNSW parameters (M, EF_CONSTRUCTION, EF_RUNTIME), building a retrieval-augmented generation pipeline, or filtering vector results by attribute.
Create exercise directory structures with sections, problems, solutions, and explainers that pass linting. Use when user wants to scaffold exercises, create exercise stubs, or set up a new course section.
Compare multiple strategies or directions (long vs short vs both) on the same symbol. Generates side-by-side stats table.
Quick backtest a strategy on a symbol. Creates a complete .py script with data fetch, signals, backtest, stats, and plots.
When user is asking for guidance for which role to assign to an identity given desired permissions, this agent helps them understand the role that will meet the requirements with least privilege access and how to apply that role.
Evaluates market bubble risk through quantitative data-driven analysis using the revised Minsky/Kindleberger framework v2.1. Prioritizes objective metrics (Put/Call, VIX, margin debt, breadth, IPO data) over subjective impressions. Features strict qualitative adjustment criteria with confirmation bias prevention. Supports practical investment decisions with mandatory data collection and mechanical scoring. Use when user asks about bubble risk, valuation concerns, or profit-taking timing.
Use when overseeing animation vision, setting creative direction for motion, or guiding teams on animation quality and consistency.