Skill UI

A comprehensive guide detailing best practices for achieving high reproducibility in recommender system research. It covers critical areas such as dataset version pinning, defining symmetric tuning protocols, selecting full-ranking metrics, handling non-determinism via multiple seeds, and structuring rigorous divergence analysis for academic publications.

Profiles a paper and matches it to suitable academic journals from an index of 743 venues, ranking candidates into reach, match, and safe categories with a resubmission ladder. Ideal for authors deciding where to submit or resubmit after rejection.

This skill performs deep 'git archaeology' by cross-referencing commit history, changelogs, and initial summaries. It extracts verified metrics like commit velocity, contributor rankings, and release timelines, generating multiple detailed reports. Use this when building a REX talk and needing factual, data-backed evidence from a source git repository.

This methodology guides developers to diagnose ambiguous failures, intermittent bugs, or performance regressions before implementing any code changes. It emphasizes separating observed symptoms from inferred causes, tracing inputs and state transitions, and ranking hypotheses based on evidence and cheap falsification value. Use this structured approach to ensure fixes are built upon a proven mechanism.

A comprehensive content methodology distilled from top-tier AI media platforms. This framework teaches how to structure high-impact articles, ranging from rapid news briefs (50+ daily updates) to deep, authoritative long-form reports. Key techniques include adopting a conflict-first narrative style, maximizing emotional intensity through exclamation marks, prioritizing Chinese cultural context over direct translation, and establishing industry authority through structured rankings and comprehensive coverage.

Coordinates discovery, matching, and workflow orchestration across agent ecosystems, automatically scanning SKILL.md, ranking relevant skills, and executing multi-step plans for complex requests.

Comprehensive skill for using Azure AI Search SDK for Python, covering vector search, hybrid search, semantic ranking, indexing, and skillsets. Ideal for implementing AI-powered search solutions with full-text and vector capabilities.

Locate, select, and verify evidence in documents or code inventories. Supports source-span extraction, passage reranking, and claim checks. Preserves citations and handles no-match outcomes using graph tools for exact code lookup. Ideal for AI agents performing evidence-based reasoning.

Run Fireworks-hosted open-weight model councils that compare responses and synthesize a final answer. This skill implements Karpathy's LLM Council concept with parallel model responses, ranking, and chairman synthesis.

This skill provides a comprehensive audit framework and optimization strategy for local SEO, specifically tailored for law firms, attorneys, and legal/professional service providers. It focuses on maximizing local visibility by optimizing Google Business Profiles (GBP), establishing critical E-E-A-T signals, and ensuring directory consistency. Use this when aiming to improve ranking in local Google packs, maps, and specialized legal directories.

Curated upstream guidance for Longbridge Research. Provides institutional data, sell-side research, and investment research frameworks including analyst ratings, consensus estimates, financial calendars, shareholder data, insider trades, short selling data, industry rankings, peer group trees, investment idea generation, investment proposals, coverage initiation, competitive analysis, financial planning, DeFi yield analysis, and on-chain data. Use when the user's goal matches the documented workflows.

Generates long-form blog posts optimized for search intent and AI answers. Includes TL;DR blocks, FAQs, internal links, and conversion CTAs to improve ranking and user engagement.