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Data & AI

Machine learning, LLMs, and data processing.

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machine-learning
10

mlx

Running and fine-tuning LLMs on Apple Silicon with MLX. Use when working with models locally on Mac, converting Hugging Face models to MLX format, fine-tuning with LoRA/QLoRA on Apple Silicon, or serving models via HTTP API.

itsmostafa
itsmostafa
data-ai
open
machine-learning
10

qlora

Memory-efficient fine-tuning with 4-bit quantization and LoRA adapters. Use when fine-tuning large models (7B+) on consumer GPUs, when VRAM is limited, or when standard LoRA still exceeds memory. Builds on the lora skill.

itsmostafa
itsmostafa
data-ai
open
llm-ai
10

prompt-exec

Execute the forged prompt exactly as written. Requires explicit consent and a ready artifact. Deletes artifact after successful execution.

JordanGunn
JordanGunn
data-ai
open
machine-learning
10

transformers

Loading and using pretrained models with Hugging Face Transformers. Use when working with pretrained models from the Hub, running inference with Pipeline API, fine-tuning models with Trainer, or handling text, vision, audio, and multimodal tasks.

itsmostafa
itsmostafa
data-ai
open
llm-ai
10

ralph-orchestrator

Orchestrates the full Ralph autonomous agent pipeline from requirements gathering to execution. Use when building new features, platforms, or complex tasks that need structured development through spec-interview, PRD generation, and autonomous implementation.

cfircoo
cfircoo
data-ai
open
llm-ai
10

claude-md-author

This skill should be used when the user asks to "create a CLAUDE.md", "write a CLAUDE.md", "set up CLAUDE.md", "configure Claude for this project", "add project instructions for Claude", "initialize Claude context", or mentions needing project-specific Claude instructions.

petekp
petekp
data-ai
open
llm-ai
10

ask-user-choice

ユーザーに質問や確認をする際に毎回発動してください。自由回答形式ではなく、明確な選択肢(1質問あたり2-4個)を持つAskUserQuestionツールを使用し、ユーザーの入力負担を軽減して意思決定を迅速化します。柔軟性のためmultiSelect trueをデフォルトにしてください。

syou6162
syou6162
data-ai
open
machine-learning
10

lora

Parameter-efficient fine-tuning with Low-Rank Adaptation (LoRA). Use when fine-tuning large language models with limited GPU memory, creating task-specific adapters, or when you need to train multiple specialized models from a single base.

itsmostafa
itsmostafa
data-ai
open
llm-ai
10

clarity-gate

Pre-ingestion verification for epistemic quality in RAG systems. Ensures documents are properly qualified before entering knowledge bases. Produces CGD (Clarity-Gated Documents) and validates SOT (Source of Truth) files.

frmoretto
frmoretto
data-ai
open
llm-ai
10

skill-capability-matcher

This skill should be used when matching user requirements to available skills from a compiled registry. It receives a skill registry (from registry-loader) and user requirements, then scores each skill based on capability alignment, producing prioritized matches with confidence scores. Triggers: "match skills to requirements", "find relevant skills for workflow", "which skill handles X", "score skill capabilities", "/build" (after registry load), "find skills for this task", "match my requirements to skills". Second step in looplia workflow building pipeline: takes user requirements and skill registry, recommends skill sequences with missions. Designs one workflow step → one skill-executor → multiple skills orchestration pattern.

memorysaver
memorysaver
data-ai
open
llm-ai
10

bootstrap

This skill should be used when the user asks to "create a bootstrap prompt", "handoff", "save session state", "continue in new session", "create handoff", "session summary for continuation", "bootstrap for fresh session", or wants to capture the current session state for resumption in a new Claude Code session.

petekp
petekp
data-ai
open
llm-ai
10

agent-development

This skill should be used when the user asks to "create an agent", "add an agent", "write a subagent", "agent frontmatter", "when to use description", "agent examples", "agent tools", "agent colors", "autonomous agent", or needs guidance on agent structure, system prompts, triggering conditions, or agent development best practices for Claude Code plugins.

basher83
basher83
data-ai
open
machine-learning
10

council

Run multi-LLM council for adversarial debate and cross-validation. Orchestrates Claude, GPT-4, and Gemini for production-grade implementation, code review, architecture design, research, and security analysis.

sherifkozman
sherifkozman
data-ai
open
llm-ai
10

writing-journal

Aggregate a writing session into a readable log + a reusable author-intent prompt.

aevatarAI
aevatarAI
data-ai
open
llm-ai
10

mcp-builder

Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).

basher83
basher83
data-ai
open
llm-ai
10

workflow-executor

This skill should be used when the user wants to execute a looplia workflow, run workflow steps, or process a workflow.md file. Use when someone says "run the looplia workflow", "execute this looplia pipeline", "/run writing-kit", "start the looplia automation", or "process these workflow steps". Architecture: One workflow step triggers one general-purpose subagent call, which then invokes skills to accomplish the step's mission. Each step = separate context window. Handles sandbox management, per-step orchestration, and validation state tracking. v0.6.9: Unified general-purpose subagent strategy for all providers (context offload).

memorysaver
memorysaver
data-ai
open
llm-ai
10

example-skill

An example skill demonstrating the Agent Skills structure with bundled resources for specialized tasks.

AmadeusITGroup
AmadeusITGroup
data-ai
open
machine-learning
10

agents

Patterns and architectures for building AI agents and workflows with LLMs. Use when designing systems that involve tool use, multi-step reasoning, autonomous decision-making, or orchestration of LLM-driven tasks.

itsmostafa
itsmostafa
data-ai
open
llm-ai
10

clarity-gate

Pre-ingestion verification for epistemic quality in RAG systems. Ensures documents are properly qualified before entering knowledge bases. Produces CGD (Clarity-Gated Documents) and validates SOT (Source of Truth) files.

frmoretto
frmoretto
data-ai
open
llm-ai
10

context-engineering

Strategies for managing LLM context windows effectively in AI agents. Use when building agents that handle long conversations, multi-step tasks, tool orchestration, or need to maintain coherence across extended interactions.

itsmostafa
itsmostafa
data-ai
open
llm-ai
10

skill-integration-templates

Standardized templates and patterns for integrating skills into agent prompts. Reduces token overhead through reusable skill reference syntax, action verbs, and progressive disclosure usage guidelines.

akaszubski
akaszubski
data-ai
open
llm-ai
9

curiosity-gap

Create engagement through strategic information gaps that drive user action. Use when designing notifications, writing headlines, planning onboarding flows, or creating content that needs to capture and hold attention.

flpbalada
flpbalada
data-ai
open
llm-ai
9

agency-ladder

Plan the v1→v2→v3 agency progression for AI features. Walk through mapping how autonomy increases over time, define promotion criteria, and generate artifacts for stakeholder alignment. Based on CC/CD framework.

breethomas
breethomas
data-ai
open
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