LLM & Agents
6763 skills in Data & AI > LLM & Agents
cognitive-mode
Comprehensive cognitive mode management skill for the VERILINGUA x VERIX x DSPy x GlobalMOO integration. Enables automatic mode selection, frame configuration, VERIX epistemic notation, and GlobalMOO optimization. Use this skill when configuring AI behavior for specific task types, optimizing prompt engineering, or ensuring epistemic consistency in responses.
testing-python
Regla 07: Pruebas. Use when writing tests, reviewing test coverage, or setting up testing.
executive-role
Defines the shared role, responsibilities, and operating principles for an Executive agent in the b00t hive.This skill uses Rhai scripting to provide model-specific directives.
advanced-coordination
Orchestrate complex, latency-aware multi-agent work with adaptive topologies, resilient routing, and evidence-backed handoffs.
expertise-manager
Route, calibrate, and continuously improve specialist coverage across domains.
semantic-search
INVOKE BEFORE writing new code to find existing implementations (DRY). Also for codebase exploration and production data search. Run: docker exec arsenal-semantic-search-cli code-search find 'query'
anthropic-prompt-engineer
Master Anthropic's prompt engineering techniques to generate new prompts or improve existing ones using best practices for Claude AI models.
skill-creator
Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Claude's capabilities with specialized knowledge, workflows, or tool integrations.
qdrant
Qdrant vector database REST API via curl. Use this skill to store, search, and manage vector embeddings.
reviewing-code
Reviews implemented code for security, quality, performance, and test coverage using specialized review agents. Use when task file is in review/ directory and requires comprehensive code review before approval. Launches test-coverage-analyzer, error-handling-reviewer, and security-reviewer in parallel.
agentdb-vector-search-optimization
AgentDB Vector Search Optimization operates on 3 fundamental principles:
research-gap-visualizer
Identify and visualize research gaps, coverage, and conflicts with explicit constraints and evidence.
testing-python
Stratégie de Tests Python. Use when writing tests, reviewing test coverage, or setting up testing.
testing-strategies
Provides test design patterns, coverage strategies, and best practices for comprehensive test suite development
grant-proposal-assistant
Use when writing or reviewing NIH, NSF, or foundation grant proposals. Invoke when user mentions specific aims, R01, R21, K-series, significance, innovation, approach section, grant writing, proposal review, research strategy, or needs help with fundable hypothesis, reviewer-friendly structure, or compliance with grant guidelines.
quality-coverage-report
Generate test coverage reports showing which code paths are tested. Use to identify untested code and improve test coverage.
agent-workflow
Expert system for designing and architecting AI agent workflows based on proven Meta methodologies. Use when users need to build AI agents, create agent workflows, solve problems using agentic systems, integrate multiple tools into agent architectures, or need guidance on agent design patterns. Helps translate business problems into structured agent solutions with clear scope, tool integration, and multi-layer architecture planning.
imgur
Upload images to Imgur for free hosting. Use this skill when you need to upload images and get public URLs for sharing or embedding in articles.
frontend-aesthetics
Distinctive frontend design principles for avoiding generic AI defaults, implementing thoughtful typography/color/animations, and creating polished user experiences based on Claude Code design research
claude-plugin-validation
Comprehensive validation system for Claude Code plugins to ensure compliance with official plugin development guidelines and prevent installation failures