oceanbase-examples
Create SQL examples for OceanBase documentation with proper formatting, meaningful names, and separated results. Use when writing or reviewing example sections in OceanBase documentation.
oceanbase-formatting
Apply OceanBase documentation formatting standards including meta tables, notice boxes, spacing, and markdown lint compliance. Use when formatting or reviewing OceanBase documentation.
oceanbase-schema-design
Schema design best practices for OceanBase database (MySQL & Oracle modes). Covers table design, partitioning strategies, table groups, index design, and schema optimization principles. Activates for schema design, table design, partition design, index design, database design, DDL.
oceanbase-sql-doc
Write and format OceanBase database SQL statement documentation following official style guidelines. Use when creating or editing SQL reference documentation for OceanBase database.
oceanbase-sql-optimization
SQL optimization best practices for OceanBase database (MySQL & Oracle modes). Covers query optimization, index usage, execution plan analysis, slow query tuning, and performance optimization techniques. Activates for SQL optimization, query performance, index design, execution plan, slow query, database performance.
oceanbase-syntax
Write SQL syntax definitions for OceanBase documentation. Syntax sections define structure without semicolons, while examples show executable statements. Use when writing syntax sections or reviewing SQL statement documentation.
experiment-tracking
Use when "experiment tracking", "MLflow", "Weights & Biases", "wandb", "model registry", "hyperparameter logging", "ML experiments", "training metrics"
agent-evaluation
Use when evaluating agent performance, building test frameworks, measuring quality, or asking about "agent evaluation", "LLM-as-judge", "agent testing", "quality metrics", "evaluation rubrics", "agent benchmarks"
codex
Use when "codex", "use gpt", "gpt-5", "openai codex", "let openai", "full-auto", "autonomous code generation"
context-compression
Use when compressing agent context, implementing conversation summarization, reducing token usage in long sessions, or asking about "context compression", "conversation history", "token optimization", "context limits", "summarization strategies"
context-degradation
Use when diagnosing agent failures, debugging lost-in-middle issues, understanding context poisoning, or asking about "context degradation", "lost in middle", "context poisoning", "attention patterns", "context clash", "agent performance drops"
context-optimization
Use when optimizing agent context, reducing token costs, implementing KV-cache optimization, or asking about "context optimization", "token reduction", "context limits", "observation masking", "context budgeting", "context partitioning"
crewai-agents
Use when "CrewAI", "multi-agent systems", "agent orchestration", "AI crews", or asking about "autonomous agents", "agent collaboration", "role-based agents", "agent workflows", "AI team coordination"
writing-plans
Use when you have a spec or requirements for a multi-step task, before touching code
writing-skills
Use when creating new skills, editing existing skills, or verifying skills work before deployment
executing-plans
Use when you have a written implementation plan to execute in a separate session with review checkpoints
dispatching-parallel-agents
Use when facing 2+ independent tasks that can be worked on without shared state or sequential dependencies
subagent-driven-development
Use when executing implementation plans with independent tasks in the current session
dspy-prompting
Use when "DSPy", "declarative prompting", "automatic prompt optimization", "Stanford NLP", or asking about "optimizing prompts", "prompt compilation", "modular LLM programming", "chain of thought", "few-shot learning"
langchain-agents
Use when "LangChain", "LLM chains", "ReAct agents", "tool calling", or asking about "RAG pipelines", "conversation memory", "document QA", "agent tools", "LangSmith"
mcp-development
Use when building "MCP server", "Model Context Protocol", creating "Claude tools", "MCP tools", or asking about "FastMCP", "MCP SDK", "tool development for LLMs", "external API integration for Claude"
memory-systems
Use when implementing agent memory, persisting state across sessions, building knowledge graphs, tracking entities, or asking about "agent memory", "knowledge graph", "entity memory", "vector stores", "temporal knowledge", "cross-session persistence"
multi-agent-patterns
Use when designing multi-agent systems, implementing supervisor patterns, coordinating multiple agents, or asking about "multi-agent", "supervisor pattern", "swarm", "agent handoffs", "orchestration", "parallel agents"
nanobanana
Use when "nanobanana", "generate image", "create image", "edit image", "AI drawing", "Gemini image", "image generation"
planning-with-files
This skill should be used when starting complex multi-step tasks, research projects, or any task requiring >5 tool calls. Implements Manus-style file-based planning with task_plan.md, findings.md, and progress.md.
plugin-development
Use when creating Claude Code plugins, writing skills, building commands, developing agents, or asking about "plugin development", "create skill", "write command", "build agent", "SKILL.md", "plugin structure", "progressive disclosure"
prompt-engineering
Use when "writing prompts", "prompt optimization", "few-shot learning", "chain of thought", or asking about "RAG systems", "agent workflows", "LLM integration", "prompt templates"
syncing-submodules
Use when running /ltk:sync-submodules, updating submodules, or needing to "sync", "merge", "adapt", "learn from" other Claude Code plugins or repos
tool-design
Use when designing agent tools, creating tool descriptions, implementing MCP tools, or asking about "tool design", "agent tools", "tool descriptions", "MCP", "function calling", "tool consolidation"
using-ltk
Use when starting any conversation - establishes how to find and use skills, requiring Skill tool invocation before ANY response including clarifying questions
dask
Use when "Dask", "parallel computing", "distributed computing", "larger than memory", or asking about "parallel pandas", "parallel numpy", "out-of-core", "multi-file processing", "cluster computing", "lazy evaluation dataframe"
data-engineering
Use when "data pipelines", "ETL", "data warehousing", "data lakes", or asking about "Airflow", "Spark", "dbt", "Snowflake", "BigQuery", "data modeling"
data-science
Use when "statistical modeling", "A/B testing", "experiment design", "causal inference", "predictive modeling", or asking about "hypothesis testing", "feature engineering", "data analysis", "pandas", "scikit-learn"
geopandas
Use when "GeoPandas", "geospatial", "GIS", "shapefile", "GeoJSON", or asking about "spatial analysis", "coordinate transformation", "spatial join", "choropleth map", "buffer analysis", "geographic data", "map visualization"
cicd-workflows
GitHub Actions and CI/CD patterns for Databricks, including automated testing, deployment, and quality gates.
data-products
Data product design patterns with contracts, SLAs, and governance for building self-serve data platforms using Data Mesh principles.
data-quality
Comprehensive data quality patterns using Great Expectations, DLT expectations, and custom validators for ensuring data reliability and trust.
databricks-asset-bundles
Modern deployment with Databricks Asset Bundles (DAB), supporting multi-environment configurations and CI/CD integration.
delta-live-tables
Delta Live Tables (DLT) pipeline patterns and examples for building declarative, self-healing data pipelines with automatic quality enforcement and lineage tracking.
delta-sharing
Delta Sharing configuration, monitoring, and recipient management for secure cross-organization data sharing.
medallion-architecture
Bronze/Silver/Gold layer design patterns and templates for building scalable data lakehouse architectures. Includes incremental processing, data quality checks, and optimization strategies.
testing-patterns
pytest fixtures and integration testing patterns for Spark applications, including DataFrame assertions and mock data generation.
access-management
RBAC/ABAC implementation patterns, least privilege access, row-level security, column masking, and access review workflows.
compliance-automation
Automated compliance checks, continuous monitoring, reporting frameworks for GDPR, HIPAA, SOC2, and CCPA compliance.
data-classification
Data classification strategies, tagging frameworks, sensitivity levels, and automated classification patterns for Unity Catalog.
unity-catalog-governance
Unity Catalog governance patterns, permissions models, security best practices, and policy enforcement for enterprise data governance.
svg-icon-maker
Generate production-quality SVG icons with COLOR support using VTracer vectorization. Converts raster images to clean, colorful SVG paths.
content-research-writer
Assists in writing high-quality content by conducting research, adding citations, improving hooks, iterating on outlines, and providing real-time feedback on each section. Transforms your writing process from solo effort to collaborative partnership.
frontend-design
Create distinctive, production-grade frontend interfaces with high design quality. Use this skill when the user asks to build web components, pages, artifacts, posters, or applications (examples include websites, landing pages, dashboards, React components, HTML/CSS layouts, or when styling/beautifying any web UI). Generates creative, polished code and UI design that avoids generic AI aesthetics.
zig-system-calls
Guides using bun.sys for system calls and file I/O in Zig. Use when implementing file operations instead of std.fs or std.posix.
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