Skill UI

This guide covers advanced retrieval strategies that significantly boost search quality beyond basic vector similarity search. Techniques include Hybrid Search (combining dense and sparse indexing), Reranking (improving result order), Relevance Feedback (guiding search with iterative user scores), and Maximal Marginal Relevance (MMR) for diversity. Use these methods when standard search results lack relevance, miss critical keywords, or exhibit poor precision.

This tool performs a rigorous Level 2 semantic epistemic review of Agent-Native Research Artifacts (ARAs). It assesses six critical dimensions—including evidence relevance, falsifiability, and methodological rigor—to determine the content's intellectual soundness. It is used after initial structural validation to provide objective, constructive criticism, scoring the work from Strong Accept to Reject.

Skill Scout is a crucial pre-creation workflow designed to prevent the duplication of effort. Before building a new skill, it systematically searches local, marketplace, GitHub, and web sources. It not only finds potential matches but also rigorously vets them for security, maintenance status, and relevance, providing the user with clear options: Use Existing, Fork/Extend, or Create New.

This skill guides users on writing highly effective media pitches and press outreach emails. Instead of generic corporate announcements, it teaches how to structure a human-to-human proposal focused on a compelling story angle, specific data points, and timely relevance. It provides detailed structures, angle development frameworks, and best practices to ensure the pitch resonates with journalists and media editors.

This pattern is designed to solve context limitations in complex multi-agent workflows. Instead of relying on a single, massive context dump, it implements a structured, multi-cycle loop (Dispatch -> Evaluate -> Refine -> Loop). This process iteratively refines the search query by scoring content relevance and identifying missing context gaps, ensuring sub-agents gather the most targeted and highly relevant information needed for tasks like debugging or feature implementation.

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 tool designed to audit the quality, relevance, and redundancy of all Claude skills and commands. It supports two modes: a rapid incremental scan for recently changed skills, and a deep full stocktake using AI judgment and expert checklists to assess viability (Keep, Improve, Update, Retire, Merge).

Identifies high-leverage backlink prospects by analyzing domains that link to multiple competitors but not the brand. It ranks these prospects using an opinionated priority score combining authority (DR), link overlap, and topical relevance. This tool is essential for planning targeted link-building campaigns, qualifying digital PR leads, or conducting deep quarterly competitive gap audits.

This guide helps academic authors structure the final 'Contribution and Implications' section of accounting manuscripts. It provides detailed guidelines on transitioning from theoretical findings to concrete, actionable suggestions for standard-setters, regulators, and practitioners, ensuring the work meets high standards of academic rigor and real-world relevance.

This skill guides authors through the rigorous requirements of American Economic Journal: Economic Policy. It helps evaluate whether an applied economics manuscript meets the journal's high bar, focusing specifically on the joint criteria of sound causal identification (DiD, IV, RDD) and clear, impactful policy relevance. Use it to re-frame arguments and check against best practices for policy evaluation.

A comprehensive guide to assessing the fit of a macroeconomics research paper for top-tier journals, particularly the American Economic Journal: Macroeconomics (AEJ: Macro). It helps researchers determine if their work possesses the required broad interest, quantitative discipline, and policy relevance to succeed at AEJ: Macro, versus more specialized venues like AER, JME, or RED. This framework guides strategic academic writing.

This guide details how the journal Agricultural Systems (AgSy) evaluates manuscripts, covering the single anonymized peer review process, desk screening criteria, and expert reviewer expectations. It helps authors pre-empt common rejection points related to systems thinking, model rigor, and decision relevance before formal submission.