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Use when evaluating Nick Sleep-style long-term compounders: scale economies shared, customer obsession, low turnover, long runway, owner culture, and value creation through lower prices.
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Use when evaluating growth stocks through O'Neil CAN SLIM: earnings acceleration, relative strength, institutional demand, market direction, base quality, and breakout discipline.
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Use when evaluating Paul Tudor Jones-style macro trend trades: major turning points, trend confirmation, risk control, stop discipline, liquidity, and not losing big.
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Use when evaluating Ed Seykota-style systematic trend following: mechanical rules, long-term trend capture, small losses, position sizing, whipsaw tolerance, and emotional discipline.
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Use when evaluating top-down macro trades, liquidity regimes, currency/rates/equity themes, concentrated risk-taking, and quick loss-cutting in a Stanley Druckenmiller style.
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Use when evaluating portfolios through Ray Dalio-style economic machine, debt cycles, diversification, risk parity, and all-weather asset allocation.
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Use when evaluating crypto charts through a CryptoCred-style structure lens: levels, confluence, market structure, risk definition, and educational technical process.
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Use when evaluating crypto networks through a Placeholder-style lens: open networks, token investment frameworks, network participation, and long-duration crypto network ownership.
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Use when evaluating crypto investments through a Multicoin-style thesis lens: high-conviction sector bets, performance chains, token value capture, and crypto-native market structure.
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Use when evaluating a decision through Charlie Munger-style mental models: inversion, incentives, quality filters, multidisciplinary reasoning, and concentrated judgment.
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Single entry skill for open-websearch setup and focused live retrieval, preferring local CLI/daemon paths while remaining compatible with workspace-exposed MCP tools.
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Use this skill to implement hybrid search combining BM25 keyword search with semantic vector search using Reciprocal Rank Fusion (RRF). **Trigger when user asks to:** - Combine keyword and semantic search - Implement hybrid search or multi-modal retrieval - Use BM25/pg_textsearch with pgvector together - Implement RRF (Reciprocal Rank Fusion) for search - Build search that handles both exact terms and meaning **Keywords:** hybrid search, BM25, pg_textsearch, RRF, reciprocal rank fusion, keyword search, full-text search, reranking, cross-encoder Covers: pg_textsearch BM25 index setup, parallel query patterns, client-side RRF fusion (Python/TypeScript), weighting strategies, and optional ML reranking.
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Use this skill to analyze an existing PostgreSQL database and identify which tables should be converted to Timescale/TimescaleDB hypertables. **Trigger when user asks to:** - Analyze database tables for hypertable conversion potential - Identify time-series or event tables in an existing schema - Evaluate if a table would benefit from Timescale/TimescaleDB - Audit PostgreSQL tables for migration to Timescale/TimescaleDB/TigerData - Score or rank tables for hypertable candidacy **Keywords:** hypertable candidate, table analysis, migration assessment, Timescale, TimescaleDB, time-series detection, insert-heavy tables, event logs, audit tables Provides SQL queries to analyze table statistics, index patterns, and query patterns. Includes scoring criteria (8+ points = good candidate) and pattern recognition for IoT, events, transactions, and sequential data.
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Use this skill for any PostgreSQL database work — table design, indexing, data types, constraints, extensions (pgvector, PostGIS, TimescaleDB), search, and migrations. **Trigger when user asks to:** - Explore an existing PostgreSQL database to understand its objects and relationships - Design or modify PostgreSQL tables, schemas, or data models - Choose data types, constraints, indexes, or partitioning strategies - Work with pgvector embeddings, semantic search, or RAG - Set up full-text search, hybrid search, or BM25 ranking - Use PostGIS for spatial/geographic data - Set up TimescaleDB hypertables for time-series data - Migrate tables to hypertables or evaluate migration candidates - Plan or execute safe schema migrations with zero downtime **Keywords:** PostgreSQL, Postgres, SQL, schema, table design, indexes, constraints, pgvector, PostGIS, TimescaleDB, hypertable, semantic search, hybrid search, BM25, time-series, migration
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Use this skill for setting up vector similarity search with pgvector for AI/ML embeddings, RAG applications, or semantic search. **Trigger when user asks to:** - Store or search vector embeddings in PostgreSQL - Set up semantic search, similarity search, or nearest neighbor search - Create HNSW or IVFFlat indexes for vectors - Implement RAG (Retrieval Augmented Generation) with PostgreSQL - Optimize pgvector performance, recall, or memory usage - Use binary quantization for large vector datasets **Keywords:** pgvector, embeddings, semantic search, vector similarity, HNSW, IVFFlat, halfvec, cosine distance, nearest neighbor, RAG, LLM, AI search Covers: halfvec storage, HNSW index configuration (m, ef_construction, ef_search), quantization strategies, filtered search, bulk loading, and performance tuning.
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World-class data science skill for statistical modeling, experimentation, causal inference, and advanced analytics. Expertise in Python (NumPy, Pandas, Scikit-learn), R, SQL, statistical methods, A/B testing, time series, and business intelligence. Includes experiment design, feature engineering, model evaluation, and stakeholder communication. Use when designing experiments, building predictive models, performing causal analysis, or driving data-driven decisions.
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Deterministic handbook-grounded retrieval and thermocouple computations for reflow profile compliance outputs such as ramp, TAL, peak, feasibility, and selection.
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Write and evaluate effective Python tests using pytest. Use when writing tests, reviewing test code, debugging test failures, or improving test coverage. Covers test design, fixtures, parameterization, mocking, and async testing.
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Download water level data from USGS using the dataretrieval package. Use when accessing real-time or historical streamflow data, downloading gage height or discharge measurements, or working with USGS station IDs.
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Use this skill when calculating control system performance metrics such as rise time, overshoot percentage, steady-state error, or settling time for evaluating simulation results.
日本語の概要は準備中です。原文の説明を表示しています。
Fetch and parse LeetCode problems with metadata, constraints, examples, hints, difficulty ratings, and related problems. Integrates with LeetCode API for comprehensive problem data retrieval.
日本語の概要は準備中です。原文の説明を表示しています。
Query expansion, HyDE, and multi-query generation for improved retrieval
日本語の概要は準備中です。原文の説明を表示しています。
Cross-encoder reranking and MMR diversity filtering for improved retrieval quality
日本語の概要は準備中です。原文の説明を表示しています。
Hybrid search combining semantic and keyword retrieval for RAG pipelines. Implement BM25 + dense vector search with fusion strategies.
日本語の概要は準備中です。原文の説明を表示しています。