13,736 mods in this category, of every kind an
agent can take. Each one carries what it costs per session, what the
scan found, and whether it is the original.
Deep learning and algorithm tutor that generates rigorous, structured tutorials combining mathematical theory with hands-on Python implementation. Use this skill whenever the user asks to learn, study, or get a tutorial on ANY technical topic — algorithms (PPO, DDPM, Transformer, DQN, SAC, etc.), ML/DL concepts…
Agentic data analysis swarm — ingest, clean, profile, analyze, visualize, report, and build interactive dashboards from CSV/Excel/JSON data. A multi-agent pipeline with specialized data-engineer, statistician, visualizer, reporter, and strategist agents coordinated by an orchestrator.
Implement, debug, run, and reproduce ML/AI paper experiments in research repositories. Use when working on PyTorch training or evaluation pipelines, baselines, ablations, dataset pipelines, environment or GPU setup, tensor-shape debugging, result export, or experiment cleanup.
Access thousands of AI prompts and skills directly in your AI coding assistant. Search prompts, discover skills, save your own, and improve prompts with AI.
★not rated 2 yesterdayA
tokens not measured
originalCC0-1.0
Design and generate AI Agent role/personality definitions using the SOUL/IDENTITY/AGENTS three-layer prompt architecture. Use when: (1) Creating a new AI Agent persona from scratch, (2) Writing or editing SOUL.md, IDENTITY.md, or AGENTS.md files, (3) Designing role prompts for AI assistants, chatbots, or autonomous…
Use when writing code in an app that does semantic search, RAG, or ingests documents into a vector database on the platform — running nearest-neighbor queries, listing/adding/removing documents, or feeding retrieved chunks into an LLM. Covers VectorDatabaseQuery(), ListDocumentsInVectorDatabase()…
Author LLM/RAG/agent evaluation suites in DeepEval that prove a feature is correct with gated numbers, not vibes. Use when asked to "eval an LLM", "test a prompt", "measure RAG quality", "check for hallucination", "score answer relevancy", "verify tool calls", or gate a release on model output quality. Ships the…
Compress LLM instruction sets, system prompts, rules, and guidelines to reduce token count while preserving behavioral intent. Use this skill whenever the user wants to shorten, truncate, optimize, or compress prompts, system instructions, CLAUDE.md files, custom instructions, rules, guidelines, or any instruction set…
Find a curated AI prompt template for any task — writing, image generation, video, or code. Use this skill when the user wants a ready-made prompt template (not a one-shot request). The skill queries a configurable prompt library backend via a documented /api/skill/ HTTP contract and returns the best match with…
Implements DataOps CI/CD with lakeFS-style branching, pre-commit data validation hooks, and deterministic RAG ingestion with vector DB as fuzzy recall fallback. Use when building data pipelines, RAG systems, or isolated dev/test data environments.
Use when the user asks to "write a prompt for DeepSeek", "compose a DeepSeek prompt", wants to send a task to a DeepSeek model, needs to launch a DeepSeek subagent. Also use when explicitly named: DeepSeek. Trigger on any request to draft, refine, or assemble a prompt targeting a DeepSeek-family model — for either…
★not rated 2 11d agoA84 tokens
originalMIT
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