Discover testing security llm ai skills, compare source repositories and read the instructions for each workflow.
Implement semantic vector search with AgentDB for intelligent document retrieval, similarity matching, and context-aware querying. Use when building RAG systems, semantic search engines, or intelligent knowledg...
Optimize AgentDB performance with quantization (4-32x memory reduction), HNSW indexing (150x faster search), caching, and batch operations. Use when optimizing memory usage, improving search speed, or scaling t...
Implement ReasoningBank adaptive learning with AgentDB's 150x faster vector database. Includes trajectory tracking, verdict judgment, memory distillation, and pattern recognition. Use when building self-learnin...
Kailash Kaizen - production-ready AI agent framework with signature-based programming, multi-agent coordination, and enterprise features. Use when asking about 'AI agents', 'agent framework', 'BaseAgent', 'mult...
{ONE_SENTENCE_PURPOSE}. Use when {TRIGGER_CONDITION}.
Merge style, lyrics, and producer notes into render-ready composed prompt. Enforces character limits, resolves tag conflicts, normalizes living artist influences, and formats with clear section tags. Use when c...
Use this skill when new users want to get started with LimaCharlie, set up their first organization, or begin collecting security data. Guides beginners through org creation and helps identify what to onboard,...
Use this skill when the user needs help deploying, managing, or understanding Sigma rules, Soteria rules, SOC Prime rules, Community rules, or any other managed rulesets in LimaCharlie.
Activate when the user needs help writing, optimizing, or understanding LimaCharlie Query Language (LCQL) queries for searching telemetry.
Use this skill when the user needs help designing, implementing, testing, or troubleshooting automated response playbooks using LimaCharlie's Playbook extension.
Use this skill when the user needs help creating, testing, validating, or troubleshooting Detection & Response (D&R) rules in LimaCharlie.
Help users optimize LimaCharlie performance, reduce costs, manage billing, and implement efficient resource management strategies.
Activate when the user needs help conducting proactive threat hunting, investigating suspicious activity, or building hypothesis-driven hunts in LimaCharlie.
Clear description of what this skill does and when Claude should use it. Include trigger keywords users might mention.
Creates and validates Claude Code skills with proper format. Use when creating new skills, writing SKILL.md files, validating existing skills, or when user mentions "skill format", "create skill", "skill templa...
This skill should be used when the user asks to "add MCP server", "integrate MCP", "configure MCP in plugin", "use .mcp.json", "set up Model Context Protocol", "connect external service", mentions "${CLAUDE_PLU...
Generate and edit images using Gemini API (Nano Banana Pro). Supports text-to-image, image editing, multi-turn refinement, Google Search grounding for factual accuracy, and composition from multiple reference i...
Coordinate Tutopanda CLI and MCP to generate, edit, inspect, and preview documentary videos (video-audio-music blueprint with FinalVideo export). Use when users ask for Tutopanda to build, edit, or review movie...
Medical document OCR processing for extracting structured clinical data from medical images (prescriptions, lab results, clinical notes). Uses Google Cloud Vision for text extraction and medical NLP for entity...
Build context-efficient, reusable skills using graph-based workflow orchestration with Claude Code subagents. Combines PocketFlow-inspired graph abstraction with multi-model optimization (Haiku for exploration,...
Multi-agent data science framework using DS-STAR (Data Science - Structured Thought and Action) architecture. Automates data analysis through collaborative AI agents with multi-model support (Haiku, Sonnet, Opu...
Design, organize, and operate Deepnote projects as the InsightPulseAI Data Lab workspace for exploration, jobs, and Superset-ready summary tables.
Use Superset-style APIs to manage workspaces, users, datasets, charts, and dashboards as code for the InsightPulseAI Data Lab platform.
Design, deploy, upgrade, and operate the InsightPulseAI Superset-based BI platform on the user's infrastructure with secure, stable, scalable configs.
The default order uses GitHub repository stars from our indexed data. Stars belong to the source repository and may be shared by multiple skills. They indicate repository interest, not skill installs or an independent quality score.