Skill UI

This tool generates sophisticated trading signals by leveraging an advanced anomaly detection engine. It scans financial assets for various market anomalies—such as spikes, drifts, and oscillations—and classifies them. It then integrates neural network prediction and searches historical pattern databases to output highly ranked, actionable trading signals, complete with confidence scores and target parameters.

A comprehensive tool for training and evaluating advanced neural network models (including LSTM, Transformer, and N-BEATS) on time-series market data. It facilitates the prediction of financial trends, generating results with confidence intervals, and comparing performance across multiple architectures. Ideal for quantitative trading research and financial forecasting.

Provides a structured workflow for systematically accessing and analyzing official intellectual property data from the USPTO. This skill covers patent search (PatentSearch API), trademark status checks (TSDR), ownership transfer tracking, and building reproducible IP landscape logs. It is designed for data collection and record verification, emphasizing the use of official APIs and rigorous logging practices. (Warning: Not for legal advice.)

This skill guides users through a comprehensive, structured design process. It helps transform vague ideas or initial concepts into detailed, validated specifications by exploring project context, proposing multiple options with trade-offs, and iteratively refining architectural details. It is essential for defining clear boundaries and requirements before any code is written, ensuring a robust and well-documented development roadmap.

This tool allows users to fine-tune the evaluation criteria for AI-generated content. Users can configure minimum scoring thresholds, adjust the relative weights of dimensions (such as brand voice, hallucination risk, and claim verification), and set composite auto-reject rules. It ensures the quality bar matches specific brand guidelines, industry needs, or content formats, making quality trade-offs explicit and adjustable.

A comprehensive tool for developing full-scale PR pitch packages. It assists users in crafting tailored pitch templates for various media types (national, trade, podcast), building precise target media lists with journalist contacts, and designing detailed outreach sequences. Ideal for proactive pitching or responding to journalist requests, ensuring brand consistency and maximizing coverage potential.

This skill guides researchers on the mandatory, rigorous evaluation of complex systems models (e.g., AgSy). It details best practices for model validation, emphasizing the comparison of observed vs. simulated data using independent, held-out datasets. Key components covered include standard fit statistics (RMSE, NSE), sensitivity analysis (identifying core drivers), uncertainty propagation, and multi-objective trade-off/scenario analysis to ensure scientific credibility.

This guide provides rigorous guidelines for creating high-quality figures and tables for complex systems manuscripts, especially in agricultural science. It emphasizes shifting focus from single-factor bar charts to systemic visualizations that reveal interactions, trade-offs (e.g., Pareto fronts), model dynamics, resource flows (Sankey diagrams), and model performance (observed-vs-simulated fit). Exhibits must be self-contained, reproducible, and convey uncertainty.

This skill guides researchers on how to transform complex agricultural systems model results into actionable, honest, and scoped implications for decision-makers. It teaches authors to move beyond merely restating results by identifying the specific actors, articulating the necessary trade-offs, and clearly defining the system boundaries and uncertainty limits, ensuring the paper informs a decision rather than just demonstrating methods.

This skill guides authors on how to position their manuscript within the complex, multidisciplinary literature of Agricultural Systems (AgSy). It ensures that the paper advances the conversation by engaging both the domain knowledge and the core modeling/systems methodologies. The process focuses on identifying unresolved systemic trade-offs, pinpointing the exact research gap, and clearly articulating the unique contribution among established alternatives.

This guide helps researchers rigorously evaluate if their project meets the criteria for a 'systems analysis' in high-impact journals. It teaches how to shift the research focus from single-factor field trials to complex systems questions that analyze interactions, trade-offs, and emergent behaviors across multiple hierarchical levels, such as the farm to the food system. Essential for properly framing scope and article type before submission.

An essential orchestrator for authors submitting manuscripts to Agricultural Systems. This tool guides users through the entire academic writing lifecycle, helping them determine the appropriate article type (e.g., Review, Perspective) and ensuring the core research question addresses true systems complexity, interactions, and trade-offs, rather than single-factor trials. It maps the manuscript stage to the necessary sub-skills.