Skill UI

A comprehensive tool for querying, storing, and managing complex knowledge across multiple agent sessions. AgentDB utilizes advanced techniques including semantic routing, hierarchical recall, causal graph construction, and context synthesis. Use this skill when your application requires robust, multi-faceted knowledge retrieval and reasoning based on structured and unstructured data. It provides a structured workflow for checking system health, starting sessions, storing knowledge in tiers (working, episodic, semantic), and searching learned patterns.

This tool performs pathfinder traversal across a knowledge graph starting from a specified seed entity. It expands outward through causal edges, calculates path relevance scores, and prunes low-similarity branches. It is ideal for conducting impact analyses, tracing dependency chains, or understanding complex relationships within a structured knowledge base.

A comprehensive guide for structuring high-impact scientific papers in advanced materials. It teaches authors how to build a cohesive narrative around a single central scientific advance, emphasizing the crucial causal chain: Structure → Property → Function. It also provides rules for optimizing the opening paragraph to serve as a self-contained abstract.

This skill provides a rigorous framework for defending the methodology of advanced educational research manuscripts, suitable for top-tier academic journals. It guides users through defining research structure across quantitative (e.g., multilevel, quasi-experimental), qualitative (e.g., ethnography, case study), and mixed methods paradigms. Focus areas include addressing rival explanations, ensuring measurement validity, establishing causal claims, and meeting stringent reporting standards (AERA).

This framework guides researchers on how to elevate an academic literature review from a mere annotated bibliography into a cohesive, argumentative piece. It teaches authors to impose a central 'spine'—such as a taxonomy, causal mechanism, or set of analytical levels—to structure the subfield's existing work, thereby generating new insights and defining the field's future agenda. Essential for advanced academic writing and synthesizing large bodies of research.

A comprehensive guide for structuring research manuscripts for top-tier academic journals (e.g., ASQ). It details the rigorous requirements for both qualitative (e.g., grounded theory, ethnography) and quantitative (e.g., causal inference, multilevel modeling) designs. Learn how to ensure theoretical fit, establish credibility, and design against alternative explanations to maximize the impact and rigor of your work.

A comprehensive guide to structuring and defending research designs across various sociological methods, including quantitative, comparative-historical, ethnographic, and computational approaches. It emphasizes building a credible link between theoretical arguments and empirical evidence, critically addressing alternative hypotheses, and defining the scope of causal claims to meet the highest academic standards.

This tool simulates the rigorous editorial process required for high-level journals in finance and economics. It guides authors to transform vague, policy-report-like drafts into precise, academically robust manuscripts. Key functions include eliminating empty-significance phrases, replacing generalizations with causal mechanisms, standardizing tense and person, structuring paragraphs with clear thesis statements, and ensuring all claims are supported by specific evidence and economic interpretation.

This guide assists users in structuring and rigorously defending the methodological design for demographic manuscripts. It provides detailed guidance on selecting and justifying advanced techniques—including life tables, decomposition analysis, survival models, Age-Period-Cohort (APC) modeling, and microsimulation. It emphasizes critical steps like establishing identification assumptions, addressing causal biases (selection and exposure), and formulating an adjudication test to rule out rival explanations, ensuring the research is methodologically robust.

This comprehensive guide provides advanced methodological strategies for authors submitting to the Journal of Economic Geography (JEG). It addresses critical challenges in establishing causal inference using spatial data, such as spatial autocorrelation, spillover effects (SUTVA violations), and structural elasticity identification. It covers modern techniques for spatial DID, Network Equilibrium Models (NEG), and qualitative case studies, ensuring methodological rigor.

This guide teaches researchers how to structure and frame academic papers, specifically for journals focusing on financial intermediation. It emphasizes moving the contribution narrative away from general finance concepts and anchoring it firmly in the roles of institutions, economic friction, causal mechanisms, and policy consequences within the financial system. Use this to strengthen abstracts and introduction paragraphs.

This skill guides the rigorous defense of research design for demographic studies, particularly those linking population dynamics to development outcomes. It assists in selecting and justifying appropriate methods—such as life tables, decomposition, event-history modeling, and age-period-cohort analysis—and critically addresses the identification of causal links between population structure and development progress. It focuses on strengthening the argument by confronting rival hypotheses and establishing methodological rigor, without writing code.