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Found 286 Skills
AgentDB memory system with HNSW vector search. Provides 150x-12,500x faster pattern retrieval, persistent storage, and semantic search capabilities for learning and knowledge management. Use when: need to store successful patterns, searching for similar solutions, semantic lookup of past work, learning from previous tasks, sharing knowledge between agents, building knowledge base. Skip when: no learning needed, ephemeral one-off tasks, external data sources available, read-only exploration.
Interview about a plan file to refine it through in-depth questioning. Use when you have a plan that needs validation, refinement, or deeper exploration before implementation. Triggers on "interview me about", "refine this plan", "question this spec".
Running and fine-tuning LLMs on Apple Silicon with MLX. Use when working with models locally on Mac, converting Hugging Face models to MLX format, fine-tuning with LoRA/QLoRA on Apple Silicon, or serving models via HTTP API.
Conduct Neovim configuration research using plugin docs and codebase exploration. Invoke for neovim research tasks.
Use when starting a session on a project, returning after time away, or before making significant changes. Essential for building comprehensive understanding of project state through total recall and deep exploration.
Core rules for bkit plugin. PDCA methodology, level detection, agent auto-triggering, and code quality standards. These rules are automatically applied to ensure consistent AI-native development. Use proactively when user requests feature development, code changes, or implementation tasks. Triggers: bkit, PDCA, develop, implement, feature, bug, code, design, document, 개발, 기능, 버그, 코드, 설계, 문서, 開発, 機能, バグ, 开发, 功能, 代码, desarrollar, función, error, código, diseño, documento, développer, fonctionnalité, bogue, code, conception, document, entwickeln, Funktion, Fehler, Code, Design, Dokument, sviluppare, funzionalità, bug, codice, design, documento Do NOT use for: documentation-only tasks, research, or exploration without code changes.
Create and configure LaunchDarkly feature flags in a way that fits the existing codebase. Use when the user wants to create a new flag, wrap code in a flag, add a feature toggle, or set up an experiment. Guides exploration of existing patterns before creating.
Conduct exhaustive, citation-rich research on any topic using all available tools: web search, browser automation, documentation APIs, and codebase exploration. Use when asked to "research X", "find out about Y", "investigate Z", "deep dive into...", "what's the current state of...", "compare options for...", "fact-check this...", or any request requiring comprehensive, accurate information from multiple sources. Prioritizes accuracy over speed, cross-references claims across sources, identifies conflicts, and provides full citations. Outputs structured findings with confidence levels and source quality assessments.
Search, query, and manage Weaviate vector database collections. Use for semantic search, hybrid search, keyword search, natural language queries with AI-generated answers, collection management, data exploration, filtered fetching, data imports from CSV/JSON/JSONL files, create example data and collection creation.
Recursive Language Models (RLM) CLI - enables LLMs to recursively process large contexts by decomposing inputs and calling themselves over parts. Use for code analysis, diff reviews, codebase exploration. Triggers on "rlm ask", "rlm complete", "rlm search", "rlm index".
Use this skill when the user uploads Excel (.xlsx/.xls) or CSV files and wants to perform data analysis, generate statistics, create summaries, pivot tables, SQL queries, or any form of structured data exploration. Supports multi-sheet Excel workbooks, aggregation, filtering, joins, and exporting results to CSV/JSON/Markdown.
Add a new skill to the LaunchDarkly agent-skills repo. Use when creating a new SKILL.md, adding a skill to the catalog, or aligning with repo conventions. Guides exploration of existing skills before creating.