Discover devops llm ai skills, compare source repositories and read the instructions for each workflow.
Guidance for text embedding retrieval tasks using sentence transformers or similar embedding models. This skill should be used when the task involves loading documents, encoding text with embedding models, comp...
Guidance for implementing neural network inference (like GPT-2) under extreme code size constraints. This skill should be used when tasks require implementing ML model inference in minimal code (code golf), par...
This skill provides guidance for implementing headless terminal interfaces that programmatically control interactive shell sessions. Use this skill when tasks involve creating terminal emulators, implementing p...
Guidance for building Caffe from source and training CIFAR-10 models. This skill applies when tasks involve compiling Caffe deep learning framework, configuring Makefile.config, preparing CIFAR-10 dataset, or t...
SDK/API patterns for configuring LLM models on Letta agents. Use when setting model handles, adjusting temperature/tokens, configuring provider-specific settings (reasoning, extended thinking), or setting up cu...
Guidance for SAM-based cell segmentation and mask conversion tasks involving MobileSAM, mask-to-polygon conversion, CSV processing, and command-line interface design. This skill applies when working with Segmen...
This skill provides guidance for training FastText text classification models with constraints on accuracy and model size. It should be used when training fastText supervised models, optimizing model size while...
Guide for using the Letta Conversations API to manage isolated message threads on agents. Use when building multi-user chat applications, session management, or any scenario requiring separate conversation cont...
Guidance for setting up HuggingFace model inference services with Flask APIs. This skill applies when downloading HuggingFace models, creating inference endpoints, or building ML model serving APIs. Use for tas...
Guidance for counting tokens in datasets, particularly from HuggingFace or similar sources. This skill should be used when tasks involve counting tokens in datasets, understanding dataset schemas, filtering by...
Meta-skill for recognizing learnings, validating improvements, and contributing back to the collective knowledge base. Use when agents discover better patterns, find gaps in existing skills, or want to improve...
AI-DLC workflow execution that loads and follows external aidlc-workflows rules to plan, design, and generate code with approval gates and aidlc-docs artifacts. Use when a user wants to run AI-DLC, needs adapti...
Command-line tools that delegate analysis tasks to AI models. Includes image description, screenshot comparison, essay generation from text, and boolean condition evaluation. Use for describing images, comparin...
New agent startup checklist for Agent Mail and Beads. Use when starting a new agent session, when the user says "prime" or "startup", or when beginning work on a multi-agent project.
Retrieve context from past sessions before implementing. Use for learned patterns, past solutions, anti-patterns, session history, or when the user mentions "recall", "memory", "history", "cass", "cm", or "what...
Multi-agent coordination with Agent Mail MCP. Use when registering agents, reserving files, sending messages, coordinating with other agents, or when the user mentions "agent mail", "coordination", "file reserv...
Resolve disagreements between agents or approaches using test-based adjudication. Use when agents disagree, when multiple valid approaches exist, when the user asks "which approach", or when making architectura...
Generate a Product Requirements Document (prd.json) for the Ralph autonomous agent loop. Use when planning a feature, starting a new project, or preparing work for Ralph to implement. Triggers on: create a prd,...
Debug AI traces, find exceptions, analyze sessions, and manage prompts via Langfuse MCP. Also handles MCP setup and configuration.
This skill should be used when the user asks to "create chatbot", "virtual agent", "VA topic", "NLU", "conversation", "chat flow", "topic block", or any ServiceNow Virtual Agent development.
This skill should be used when the user asks about "snow-flow commands", "CLI commands", "how to start", "swarm", "sparc", "orchestrator", "agent spawn", "memory", "task", or needs guidance on Snow-Flow CLI ope...
This skill should be used when the user asks to "predictive intelligence", "machine learning", "ML", "classification", "similarity", "clustering", "prediction", "AI", or any ServiceNow Predictive Intelligence d...
Synthesize consensus implementation plan from multi-agent debate reports using external AI review
Create, update, and validate repository skills under your agent’s skills directory (Codex: `.codex/skills/`, Claude: `.claude/skills/`) so they match the real codebase and `AGENTS.md` rules; tune YAML `descript...
The default order uses GitHub repository stars from our indexed data. Stars belong to the source repository and may be shared by multiple skills. They indicate repository interest, not skill installs or an independent quality score.