domain cluster

Data & AI

Machine learning, LLMs, and data processing.

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llm-ai
17

interview

Conducts structured interviews to extract requirements, constraints, and design decisions. Use when the user invokes /interview or needs to discover requirements through conversation.

corca-ai
corca-ai
data-ai
open
llm-ai
17

review-management

Optimize review scores and leverage user-generated content for AI visibility and brand trust.

majesticlabs-dev
majesticlabs-dev
data-ai
open
llm-ai
17

power-words

Enhance copy with emotional trigger words from 21 psychological categories. Transform bland text into compelling, conversion-focused content.

majesticlabs-dev
majesticlabs-dev
data-ai
open
data-engineering
17

polars-expertise

This skill should be used when the user asks about Polars DataFrame library (Apache Arrow) for Python or Rust. Triggers: "polars expressions", "lazy vs eager", "scan_parquet streaming", "convert pandas to polars", "pyspark to polars", "kdb to polars", "group_by_dynamic", "rolling_mean", "polars window functions", "asof join", "polars GPU", "polars parquet", "LazyFrame". Time series: OHLCV resampling, rolling windows, financial data patterns. Performance: native expressions over map_elements, early projection, categorical types, streaming.

DeevsDeevs
DeevsDeevs
data-ai
open
data-engineering
17

data-profiler

Generate comprehensive data profiles for DataFrames. Use for EDA, data discovery, and understanding dataset characteristics.

majesticlabs-dev
majesticlabs-dev
data-ai
open
data-analysis
17

anomaly-detector

Detect anomalies in data using statistical and ML methods. Z-score, IQR, Isolation Forest, and time-series anomalies.

majesticlabs-dev
majesticlabs-dev
data-ai
open
data-engineering
17

test-fixture-generator

Generate synthetic test data with edge cases for ETL pipeline testing.

majesticlabs-dev
majesticlabs-dev
data-ai
open
data-engineering
17

data-validation

Data validation patterns and pipeline helpers. Custom validation functions, schema evolution, and test assertions.

majesticlabs-dev
majesticlabs-dev
data-ai
open
data-engineering
17

pydantic-validation

Record-level data validation using Pydantic models. Field validators, model validators, and batch validation patterns.

majesticlabs-dev
majesticlabs-dev
data-ai
open
data-engineering
17

pandera-validation

DataFrame schema validation using pandera. Schema definitions, column checks, and decorator-based validation.

majesticlabs-dev
majesticlabs-dev
data-ai
open
data-engineering
17

litestream-coder

This skill guides configuring Litestream for continuous SQLite backup in Rails 8+ apps. Use when setting up production backups for SQLite databases (Solid Queue, Solid Cache, Solid Cable).

majesticlabs-dev
majesticlabs-dev
data-ai
open
data-engineering
17

parquet-coder

Columnar file patterns including partitioning, predicate pushdown, and schema evolution.

majesticlabs-dev
majesticlabs-dev
data-ai
open
data-engineering
17

csv-wrangler

Handle messy CSVs with encoding detection, delimiter inference, and malformed row recovery.

majesticlabs-dev
majesticlabs-dev
data-ai
open
data-engineering
17

pandas-coder

DataFrame manipulation with chunked processing, memory optimization, and vectorized operations.

majesticlabs-dev
majesticlabs-dev
data-ai
open
data-engineering
17

etl-incremental-patterns

Incremental data loading patterns including backfill strategies, CDC, timestamp-based loads, and pipeline orchestration.

majesticlabs-dev
majesticlabs-dev
data-ai
open
llm-ai
17

claude-agent-development

This skill should be used when creating agents, writing agent frontmatter, configuring subagents, or when "create agent", "agent.md", "subagent", or "Task tool" are mentioned.

outfitter-dev
outfitter-dev
data-ai
open
llm-ai
17

langchain-agents

Expert guidance for building LangChain agents with proper tool binding, memory, and configuration. Use when creating agents, configuring models, or setting up tool integrations in LangConfig.

LangConfig
LangConfig
data-ai
open
llm-ai
17

skill-design-philosophy

Core philosophy for designing Claude Code skills - when to use skills vs agents, the knowledge test, and what makes skills valuable. Use when deciding component type or evaluating skill quality.

majesticlabs-dev
majesticlabs-dev
data-ai
open
llm-ai
17

vvm

VVM (Vibe Virtual Machine) is a language for agentic programs where the LLM is the runtime. Activate when: running .vvm files, mentioning VVM, calling /vvm-boot, /vvm-run, /vvm-compile, or orchestrating multi-agent workflows. Read spec.md for the language specification and vvm.md for execution semantics.

karanchawla
karanchawla
data-ai
open
llm-ai
17

context-manager

Manages permanent memory storage for decisions, blockers, context, preferences, and procedures. Use when user says "remember", "save this decision", "what did we decide", "recall", "search memories", "any blockers", or when making important architectural decisions. Provides SDAM compensation through external memory.

Toowiredd
Toowiredd
data-ai
open
llm-ai
17

skills-development

This skill should be used when creating skills, writing SKILL.md files, or when "create skill", "new skill", "validate skill", or "SKILL.md" are mentioned.

outfitter-dev
outfitter-dev
data-ai
open
llm-ai
17

mcp-builder

Comprehensive guide for creating Model Context Protocol (MCP) servers. Use when building MCP servers, integrating external APIs, or creating tool interfaces for LLMs.

LangConfig
LangConfig
data-ai
open
llm-ai
17

claude-code-configuration

This skill should be used when configuring Claude, setting up MCP servers, or when "settings.json", "claude_desktop_config", "MCP server", or "Claude config" are mentioned.

outfitter-dev
outfitter-dev
data-ai
open
llm-ai
17

codex-configuration

This skill should be used when configuring Codex CLI, setting up profiles, or when "config.toml", "sandbox mode", "Codex config", or "approval policy" are mentioned.

outfitter-dev
outfitter-dev
data-ai
open
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