Agent quality is difficult to measure because outputs vary and may have several valid forms. This skill builds repeatable rubrics, tests, gates, and monitoring.

Agent decisions become difficult to explain when beliefs, goals, and commitments lack formal structure. This skill models BDI chains with RDF, SPARQL, provenance, and temporal validity.

Maintaining current A-share market data across several tables is slow and operationally complex. This skill configures, updates, and queries a compatible local DuckDB database through MCP tools.

Large A-share datasets make factor testing and strategy validation slow and inconsistent. QuantAll runs vectorized local analysis and returns measurable backtest, IC, screening, and visualization results.

Azure Data Explorer data can be hard to inspect without the right KQL structure and schema context. This skill helps Claude, Codex, and Claude Code build focused KQL queries, explore schemas, and troubleshoot ADX results.

Azure spending can be difficult to explain and control. This skill queries costs, forecasts spending, and produces evidence-based optimization recommendations.

Prediction market changes can be difficult to track across frequent updates. This skill polls approved feeds and formats alerts for notable events and movements.

WeChat Mac data is encrypted and difficult to search or export. This skill builds a local vault for authorized queries, exports, and summaries.

Technical analysis often requires several methods and consistent data preparation. This skill applies nine structured frameworks to Longbridge OHLCV data and explains each result.

Quantitative research requires consistent data, statistical methods, and validation. This skill structures Longbridge workflows for analysis, screening, optimization, execution, and hedging.

Brokerage data and portfolio decisions are difficult to review across separate screens. This skill retrieves Longbridge account data and provides structured analysis and controlled actions.

Market data is fragmented across symbols, sessions, and formats. This skill retrieves Longbridge data and converts it into clear, sourced analysis.

Market research and account analysis often require several disconnected tools. This skill organizes Longbridge CLI, MCP, and SDK workflows for data, content, portfolios, and development.

Merchants need current supplier product data before choosing inventory. This skill queries LegendShop product, inventory, price, and balance data through the platform API.

Database schema design can become fragmented across notes, SQL drafts, and diagrams. DB Craft opens a local visual studio to model tables, validate structure, and export SQL.

Large tabular datasets often exceed local memory and make pandas workflows slow. This skill guides Claude, Codex, and Claude Code through Vaex workflows for lazy analysis, conversion, visualization, and ML.

Transformer workflows often require many APIs for inference, generation, tokenization, and training. This skill gives Claude, Codex, and Claude Code focused guidance for using Hugging Face Transformers.

Symbolic math tasks can become error-prone when formulas need exact algebraic results. This skill guides Claude, Codex, and Claude Code through SymPy workflows for solving, simplifying, differentiating, integrating, and generating mathematical output.

Protein interaction analysis often requires manual API queries and careful identifier mapping. This skill queries STRING, maps identifiers, retrieves networks, and summarizes enrichment results.

Reinforcement learning setup is easy to misconfigure. This skill guides SB3 training, custom environments, callbacks, evaluation, and model persistence.