Total 43,773 skills, AI & Machine Learning has 6988 skills
Showing 12 of 6988 skills
Create, update, refactor, explain, or review Semantic Kernel solutions using shared guidance plus language-specific references for .NET and Python.
Instrument Python LLM apps, build golden datasets, write eval-based tests, run them, and root-cause failures — covering the full eval-driven development cycle. Make sure to use this skill whenever a user is developing, testing, QA-ing, evaluating, or benchmarking a Python project that calls an LLM, even if they don't say "evals" explicitly. Use for making sure an AI app works correctly, catching regressions after prompt changes, debugging why an agent started behaving differently, or validating output quality before shipping.
Multi-agent CLI system for autonomous novel writing, auditing, and revision with human review gates
Skill Map Viewer. Scans all installed skills and renders a visual overview — you can check the name, version, description, and category at a glance. This tool is triggered when the user says 'skills', '技能', '技能地图', 'skill map', '我有哪些技能', '看看技能', '列出技能', 'list skills'. It also activates when the user asks about available or installed skills.
Paper Workflow: Read papers and create reading cards in one go. Accepts one or more arXiv links, paper URLs, PDFs, or paper titles. For each paper, it runs ljg-paper (generates org-format analysis) followed by ljg-card -l (generates long-form reading card PNG). Trigger this workflow when the user says '论文流', 'paper flow', '读论文并做卡片', '论文卡片', or provides multiple papers and requires both analysis and reading cards.
Investment Analysis: Generate an in-depth investment analysis report. We do not conduct traditional investment analysis—the core judgment is whether the project is an "Order-Creating Machine". Activate this when the user says "investment report", "investment analysis", "analyze this project", "write an investment report", "investment report", "invest analysis", or provides entrepreneur conversation records for investment evaluation. Also activate when the user pastes or references meeting notes, pitch decks, or founder interviews and requests analysis.
Deep concept anatomist that deconstructs any concept through 8 exploration dimensions (history, dialectics, phenomenology, linguistics, formalization, existentialism, aesthetics, meta-philosophy) and compresses insights into an epiphany. Use when user asks to explain, dissect, or deeply understand a concept, term, or idea. Triggers on '解剖概念', '概念解剖', 'explain concept', 'learn concept', '/ljg-learn'. Produces org-mode output.
Main Copilot skill gate for the Fusion ecosystem — cross-domain router. USE FOR: routing between different Fusion domains (skills, issues, PRs, reviews) when the right domain skill is unclear; getting install guidance for missing skills. DO NOT USE FOR: skill lifecycle operations (use fusion-skills directly), tasks where a specific Fusion skill is already active.
Evaluate any address for home buyers and renters. Get nearby schools, transit, grocery stores, parks, restaurants, and walkability using Camino AI's location intelligence.
Provides Qdrant vector database integration patterns with LangChain4j. Handles embedding storage, similarity search, and vector management for Java applications. Use when implementing vector-based retrieval for RAG systems, semantic search, or recommendation engines.
Design economic systems for fictional worlds. Use when worldbuilding needs currencies, trade networks, resource economies, or when economic pressures should drive plot and character motivation.
Design and implement a complete ML pipeline for: $ARGUMENTS