machine-learning
54.3K
grpo-rl-training
Expert guidance for GRPO/RL fine-tuning with TRL for reasoning and task-specific model training
NousResearch
data-ai
sorting
stars
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query
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machine-learning
54.3K
peft-fine-tuning
Parameter-efficient fine-tuning for LLMs using LoRA, QLoRA, and 25+ methods. Use when fine-tuning large models (7B-70B) with limited GPU memory, when you need to train <1% of parameters with minimal accuracy loss, or for multi-adapter serving. HuggingFace's official library integrated with transformers ecosystem.
NousResearch
data-ai
machine-learning
54.3K
pytorch-fsdp
Expert guidance for Fully Sharded Data Parallel training with PyTorch FSDP - parameter sharding, mixed precision, CPU offloading, FSDP2
NousResearch
data-ai
machine-learning
54.3K
fine-tuning-with-trl
Fine-tune LLMs using reinforcement learning with TRL - SFT for instruction tuning, DPO for preference alignment, PPO/GRPO for reward optimization, and reward model training. Use when need RLHF, align model with preferences, or train from human feedback. Works with HuggingFace Transformers.
NousResearch
data-ai
llm-ai
52.8K
meeting-insights-analyzer
Analyzes meeting transcripts and recordings to uncover behavioral patterns, communication insights, and actionable feedback. Identifies when you avoid conflict, use filler words, dominate conversations, or miss opportunities to listen. Perfect for professionals seeking to improve their communication and leadership skills.
ComposioHQ
data-ai
llm-ai
52.6K
mem0
Integrate Mem0 Platform into AI applications for persistent memory, personalization, and semantic search. Use this skill when the user mentions "mem0", "memory layer", "remember user preferences", "persistent context", "personalization", or needs to add long-term memory to chatbots, agents, or AI apps. Covers Python and TypeScript SDKs, framework integrations (LangChain, CrewAI, Vercel AI SDK, OpenAI Agents SDK, Pipecat), and the full Platform API. Use even when the user doesn't explicitly say "mem0" but describes needing conversation memory, user context retention, or knowledge retrieval across sessions.
mem0ai
data-ai
llm-ai
52.6K
mem0
Mem0 Platform SDK for adding persistent memory to AI applications. TRIGGER when: user mentions "mem0", "MemoryClient", "memory layer", "remember user preferences", "persistent context", "personalization", or needs to add long-term memory to chatbots, agents, or AI apps. Covers Python SDK (mem0ai), TypeScript SDK (mem0ai), and framework integrations (LangChain, CrewAI, OpenAI Agents SDK, Pipecat, LlamaIndex, AutoGen, LangGraph). Also covers the open-source self-hosted Memory class. This is the DEFAULT mem0 skill for ambiguous queries. DO NOT TRIGGER when: user asks about CLI commands, terminal usage, or shell scripts (use mem0-cli), or Vercel AI SDK / @mem0/vercel-ai-provider / createMem0 (use mem0-vercel-ai-sdk).
mem0ai
data-ai
llm-ai
52.6K
mem0-vercel-ai-sdk
Mem0 provider for Vercel AI SDK (@mem0/vercel-ai-provider). TRIGGER when: user mentions "vercel ai sdk", "@mem0/vercel-ai-provider", "createMem0", "retrieveMemories", "addMemories", "getMemories", "searchMemories", "mem0 vercel", "AI SDK provider", "AI SDK memory", or is using generateText/streamText with mem0. Also triggers for Next.js apps needing memory-augmented AI. DO NOT TRIGGER when: user asks about direct Python/TS SDK calls without Vercel (use mem0 skill), or CLI terminal commands (use mem0-cli skill).
mem0ai
data-ai
data-engineering
51.4K
para-memory-files
File-based memory system using Tiago Forte's PARA method. Use this skill whenever you need to store, retrieve, update, or organize knowledge across sessions. Covers three memory layers: (1) Knowledge graph in PARA folders with atomic YAML facts, (2) Daily notes as raw timeline, (3) Tacit knowledge about user patterns. Also handles planning files, memory decay, weekly synthesis, and recall via qmd. Trigger on any memory operation: saving facts, writing daily notes, creating entities, running weekly synthesis, recalling past context, or managing plans.
paperclipai
data-ai
llm-ai
51.4K
agent-builder
Design and build AI agents for any domain. Use when users: (1) ask to "create an agent", "build an assistant", or "design an AI system" (2) want to understand agent architecture, agentic patterns, or autonomous AI (3) need help with capabilities, subagents, planning, or skill mechanisms (4) ask about Claude Code, Cursor, or similar agent internals (5) want to build agents for business, research, creative, or operational tasks Keywords: agent, assistant, autonomous, workflow, tool use, multi-step, orchestration
shareAI-lab
data-ai
llm-ai
47.6K
knowledge-agent
Build and query AI-powered knowledge bases from claude-mem observations. Use when users want to create focused "brains" from their observation history, ask questions about past work patterns, or compile expertise on specific topics.
thedotmack
data-ai
llm-ai
47.6K
mem-search
Search claude-mem's persistent cross-session memory database. Use when user asks "did we already solve this?", "how did we do X last time?", or needs work from previous sessions.
thedotmack
data-ai
llm-ai
45.9K
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).
anthropics
data-ai
llm-ai
44.3K
bmad-document-project
Document brownfield projects for AI context. Use when the user says "document this project" or "generate project docs"
bmad-code-org
data-ai
llm-ai
44.3K
bmad-create-architecture
Create architecture solution design decisions for AI agent consistency. Use when the user says "lets create architecture" or "create technical architecture" or "create a solution design"
bmad-code-org
data-ai
llm-ai
44.3K
bmad-generate-project-context
Create project-context.md with AI rules. Use when the user says "generate project context" or "create project context"
bmad-code-org
data-ai
llm-ai
44.3K
bmad-party-mode
Orchestrates group discussions between installed BMAD agents, enabling natural multi-agent conversations where each agent is a real subagent with independent thinking. Use when user requests party mode, wants multiple agent perspectives, group discussion, roundtable, or multi-agent conversation about their project.
bmad-code-org
data-ai
data-engineering
43.8K
syncable-entity-cache-and-transform
Create cache services and transformation utilities for syncable entities in Twenty. Use when implementing entity-to-flat conversions, input DTO transpilation to universal flat entities, or cache recomputation for syncable entities.
twentyhq
data-ai
machine-learning
39.3K
filters-and-postfx
Use this skill when applying visual filters or post-processing effects in Phaser 4. Covers bloom, blur, glow, color matrix, barrel distortion, displacement, custom shaders, and the filter pipeline. Triggers on: filter, post-processing, shader, bloom, blur, glow, color effects.
phaserjs
data-ai
machine-learning
39.3K
geometry-and-math
Use this skill when using Phaser 4 math and geometry utilities. Covers vectors, rectangles, circles, triangles, polygons, random number generation, angles, distance, interpolation, and snapping. Triggers on: Vector2, Rectangle, Circle, math, distance, angle, random, lerp.
phaserjs
data-ai
machine-learning
39.3K
tweens
Use this skill when animating properties over time in Phaser 4. Covers tweens, tween chains, easing functions, stagger, yoyo, repeat, callbacks, number tweens, and the TweenManager. Triggers on: tween, ease, animate, this.tweens.add, tween chain, stagger.
phaserjs
data-ai
machine-learning
39.3K
v4-new-features
Use this skill when learning about new features, game objects, components, and rendering capabilities added in Phaser 4. Covers Filters, RenderNodes, CaptureFrame, Gradient, Noise, SpriteGPULayer, TilemapGPULayer, Lighting component, RenderSteps, and new tint modes. Triggers on: new in v4, Phaser 4 features, RenderNode, SpriteGPULayer, CaptureFrame, Gradient game object, Noise game object, new tint modes. For migrating v3 code to v4, see the v3-to-v4-migration skill instead.
phaserjs
data-ai