Topic: llm
10,059 skills in this topic.
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rag-retrieval
Retrieval-Augmented Generation patterns for grounded LLM responses. Use when building RAG pipelines, embedding documents, implementing hybrid search, contextual retrieval, HyDE, agentic RAG, multimodal RAG, query decomposition, reranking, or pgvector search.
yonatangross/orchestkit 143
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issue-progress-tracking
Auto-updates GitHub issues with commit progress. Use when starting work on an issue, tracking progress during implementation, or completing work with a PR.
yonatangross/orchestkit 143
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design-context-extract
Extract design DNA from existing app screenshots or live URLs using Google Stitch. Produces color palettes, typography specs, spacing tokens, and component patterns as design-tokens.json or Tailwind config. Use when auditing an existing design, creating a design system from a live app, or ensuring new pages match an established visual identity.
yonatangross/orchestkit 143
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testing-patterns
Redirect — testing-patterns was split into 5 focused sub-skills. Use when looking for testing-patterns, writing tests, or test automation. Redirects to testing-unit, testing-e2e, testing-integration, testing-llm, or testing-perf.
yonatangross/orchestkit 143
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quality-gates
Use when assessing task complexity, before starting complex tasks, when stuck after multiple attempts, or reviewing code against best practices. Provides quality-gates scoring (1-5), escalation workflows, and pattern library management.
yonatangross/orchestkit 143
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interaction-patterns
UI interaction design patterns for skeleton loading, infinite scroll with accessibility, progressive disclosure, modal/drawer/inline selection, drag-and-drop with keyboard alternatives, tab overflow handling, and toast notification positioning. Use when implementing loading states, content pagination, disclosure patterns, overlay components, reorderable lists, or notification systems.
yonatangross/orchestkit 143
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demo-producer
Creates polished demo videos for skills, tutorials, and CLI demonstrations. Use when producing video showcases, marketing content, or terminal recordings.
yonatangross/orchestkit 143
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testing-llm
LLM and AI testing patterns — mock responses, evaluation with DeepEval/RAGAS, structured output validation, and agentic test patterns (generator, healer, planner). Use when testing AI features, validating LLM outputs, or building evaluation pipelines.
yonatangross/orchestkit 143
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python-backend
Python backend patterns for asyncio, FastAPI, SQLAlchemy 2.0 async, and connection pooling. Use when building async Python services, FastAPI endpoints, database sessions, or connection pool tuning.
yonatangross/orchestkit 143
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implement
Full-power feature implementation with parallel subagents. Use when implementing, building, or creating features.
yonatangross/orchestkit 143
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database-patterns
Database design and migration patterns for Alembic migrations, schema design (SQL/NoSQL), and database versioning. Use when creating migrations, designing schemas, normalizing data, managing database versions, or handling schema drift.
yonatangross/orchestkit 143
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sec-context-depth
Comprehensive AI code security review using 27 sec-context anti-patterns. Use for code review when security vulnerabilities are suspected, especially for AI-generated code.
alfredolopez80/multi-agent-ralph-loop 115
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parallel
Run multiple Ralph loops concurrently for independent tasks. Supports all 6 ralph-* teammates (coder, reviewer, tester, researcher, frontend, security). Manages parallel agent execution with proper isolation and result aggregation. Use when: (1) multiple independent fixes needed, (2) parallel reviews required, (3) batch processing tasks. Triggers: /parallel, 'parallel loops', 'concurrent execution', 'run in parallel', 'batch'.
alfredolopez80/multi-agent-ralph-loop 115
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research-blockchain
Senior Blockchain Architect research agent using Zai MCP for comprehensive analysis of EVM chains, perpetual DEX architectures, CEX integrations, and DeFi-TradFi bridges. Use for: blockchain research, protocol comparisons, technical feasibility studies, security audits, compliance analysis, architecture blueprints. Triggers: /research-blockchain, 'blockchain research', protocol comparisons.
alfredolopez80/multi-agent-ralph-loop 115
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research
Comprehensive research skill using Zai MCP web search and native Claude Code tools
alfredolopez80/multi-agent-ralph-loop 115
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retrospective
Analyze completed tasks to improve the Ralph system. Saves learnings to living knowledge vault and coordinates insights across 6 ralph-* teammates.
alfredolopez80/multi-agent-ralph-loop 115
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adr
Architecture Decision Records management. Actions: create (new ADR), list (show all), search (find by keyword). Use when: (1) making architecture decisions, (2) choosing between technologies, (3) documenting trade-offs. Triggers: /adr, 'architecture decision', 'decision record', 'document decision'.
alfredolopez80/multi-agent-ralph-loop 115
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openai-docs
Access OpenAI developer documentation via Context7 MCP. Provides up-to-date docs for Codex CLI, OpenAI API, Python/Node SDKs, Agents SDK, and MCP configuration. Use when: (1) configuring Codex CLI or MCP servers, (2) writing OpenAI API integrations, (3) building agents with OpenAI SDKs, (4) troubleshooting Codex execution. Triggers: 'openai docs', 'codex documentation', 'openai api reference', 'codex mcp', 'agents sdk'.
alfredolopez80/multi-agent-ralph-loop 115
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glm5-parallel
Model-agnostic parallel execution with Agent Teams coordination
alfredolopez80/multi-agent-ralph-loop 115
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orchestrator
Full orchestration workflow with swarm mode: evaluate -> clarify -> classify -> persist -> plan mode -> spawn teammates -> execute -> validate -> retrospective. Use when: (1) implementing features, (2) complex refactoring, (3) multi-file changes, (4) tasks requiring coordination. Triggers: /orchestrator, /orch, 'orchestrate', 'full workflow', 'implement feature'.
alfredolopez80/multi-agent-ralph-loop 115
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glm-mcp
Custom skill for glm-mcp
alfredolopez80/multi-agent-ralph-loop 115
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gates
9-language quality gate validation: linting, formatting, type checking, and test execution. Validates code changes meet quality standards before completion. Use when: (1) after code implementation, (2) before PR creation, (3) as part of /orchestrator Step 6, (4) manual quality check. Triggers: /gates, 'quality gates', 'run validation', 'check quality', 'validate code'.
alfredolopez80/multi-agent-ralph-loop 115
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spec
Produce a verifiable technical specification before coding. 6 mandatory sections: Interfaces, Behaviors, Invariants (from Aristotle Phase 2), File Plan, Test Plan, Exit Criteria (executable bash commands + expected results). Use when: (1) before implementing features with complexity > 4, (2) as Step 1.5 in orchestrator workflow, (3) when requirements need formalization. Triggers: /spec, 'create spec', 'write specification', 'technical spec'.
alfredolopez80/multi-agent-ralph-loop 115
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curator-repo-learn
Learn patterns from a specific GitHub repository. Clones, analyzes code structure, extracts patterns, populates procedural memory AND syncs to Obsidian vault for Graph View visualization. Use for: targeted learning from known quality repos, quick knowledge acquisition, specific pattern extraction. Triggers: /repo-learn, /curator-repo-learn, 'learn from repo'.
alfredolopez80/multi-agent-ralph-loop 115