How real projects summarise themselves for language models.
LangChainllms.txtlangchain-ai/langgraphjs/docs/docs/llms.txt
server locally and interact with it using REST API and LangGraph Studio Web UI. - [Deploy with LangGraph Cloud Quickstart](https://docs.langchain.com/oss/javascript/langgraph/cloud/quick_start/): Deploy a LangGraph app using LangGraph Cloud. ## Concepts
Microsoftllms.txtmicrosoft/skills/docs/llms-full.txt
application development. It combines production-grade infrastructure with friendly interfaces for building agents, deploying models, and developing generative AI applications. ## Key Information **Portal**: https://ai.azure.com **SDK Installation**: ```bash pip install
Microsoftllms.txtmicrosoft/skills/docs/llms.txt
application development. It provides a comprehensive set of AI capabilities for building agents, deploying models, and developing generative AI applications with built-in enterprise-readiness including tracing, monitoring, evaluations
AWSllms.txtaws/sagemaker-python-sdk/llms.txt
Instructions for LLM agents (SageMaker Python SDK) - **SDK-first:** for any SageMaker task (train, deploy, process, pipelines), use the **SageMaker Python SDK v3** as the primary interface. Do not drop
tractorjuicellms.txttractorjuice/arc-kit/docs/llms.txt
# ArcKit > ArcKit is The Enterprise Architecture Governance Harness — an open-source toolkit covering strategy
mrgooniellms.txtmrgoonie/claudekit-skills/.claude/skills/claude-code/llms.txt
references/configuration.md ### Enterprise Features - Identity & Access Management (SSO, RBAC) - Security & Compliance (sandboxing, audit logging, certifications) - Deployment options (Bedrock, Vertex AI, self-hosted) - Monitoring & Analytics - Network configuration - See: references/enterprise-features.md ### IDE Integration - Visual
Googlellms.txtgoogle-gemini/genai-processors/llms.txt
framework logic. * `development/caching.md` / `development/tracing.md`: Optimizations and tracing. * `rapid-prototyping/ai-studio.md` / `rapid-prototyping/cli.md`: App deployment references. * **Examples** (`examples/` directory): * `chat.py`: Standard chatbot architecture. * `live_simple_cli.py` / `realtime_simple_cli.py`: Streaming architectures. * `research/`: Modular multi
Lumiwealthllms.txtLumiwealth/lumibot/llms-full.txt
Broker authentication, account permissions, supported order types, and data access still need setup. See Deploy a LumiBot Trading Strategy and the relevant broker documentation. Add AI only after the port
NVIDIAllms.txtNVIDIA/aistore/docs/llms.txt
including sharding, ETL, batch operations, and PyTorch/TensorFlow integration. ## Documentation - [Getting Started](https://aistore.nvidia.com/docs/getting_started): Deploy AIStore from single machine to bare-metal cluster - [Architecture Overview](https://aistore.nvidia.com/docs/overview): Proxy nodes
Microsoftllms.txtmicrosoft/WhatTheHack/068-AzureOpenAIApps/Student/Resources/data/mcp-info/llms-full.txt
BeeAI Framework [BeeAI Framework](https://i-am-bee.github.io/beeai-framework) is an open-source framework for building, deploying, and serving powerful agentic workflows at scale. The framework includes the **MCP Tool**, a native
NVIDIAllms.txtNVIDIA/dcgm-exporter/llms.txt
DCGM Exporter Metrics and Deployment Authoring Contract This file is for LLMs and agents generating or modifying DCGM Exporter metrics, configuration, deployment examples, and validation plans. Current repository code
patrickchughllms.txtpatrickchugh/terravision/docs/llms-full.txt
exactly this format, so the same tooling works for diagrams of what is actually deployed. --- # TerraVision node types Every key or value in a TerraVision graph is ` . `. The ` ` selects
sceneviewllms.txtsceneview/sceneview/llms.txt
# SceneView > Declarative 3D and AR SDK for Jetpack Compose (Filament, ARCore), SwiftUI (RealityKit, ARKit
ksimbackllms.txtksimback/hermes-ecosystem/llms-full.txt
autonomous, self-improving AI agent with persistent memory, auto-generated skills, and multi-platform deployment — MIT licensed, 57k+ stars. > > **Live site:** [hermesatlas.com](https://hermesatlas.com) · **Last updated:** 2026-04-11 · **Hermes
ksimbackllms.txtksimback/hermes-ecosystem/llms.txt
Masterclass - [Tonbi's Hermes Agent Masterclass](https://hermesatlas.com/masterclass/): Ten video modules covering setup, deployment, memory, skills, models, tools, automation, subagents, profiles, Kanban, and security, with transcript-derived field notes
LING71671llms.txtLING71671/open-reverselab/docs/llms-full.txt
# ReverseLab — Full Knowledge Base Dump for LLM Ingestion Total articles: 183 Generated: 2026-08
fastcrwllms.txtfastcrw/crw/docs/llms.txt
related integrations - [Agent Onboarding](https://raw.githubusercontent.com/fastcrw/crw/main/docs/docs/agent-onboarding.md): Machine-readable guidance for tool-using agents ## Deploy - [Self-Hosting](https://raw.githubusercontent.com/fastcrw/crw/main/docs/docs/self-hosting.md): Local and private deployment path - [Docker](https://raw.githubusercontent.com/fastcrw/crw/main/docs/docs/docker.md): Container
NirDiamantllms.txtNirDiamant/Agent_Memory_Techniques/llms.txt
long-term storage, cognitive architectures, retrieval patterns, frameworks (Mem0, Letta/MemGPT, Zep, Graphiti), and production deployment. Each notebook is paired with a sub-README that explains the technique, when
hoangsonwwllms.txthoangsonww/Claude-Code-Agent-Monitor/llms.txt
detailed Markdown files covering installation, setup, architecture, API, hooks, database schema, MCP integration, plugins, deployment, and internationalization. ## Core documentation - [README](https://raw.githubusercontent.com/hoangsonww/Claude-Code-Agent-Monitor/master/README.md): Install, features, npm scripts, API summary, deployment
RyanAlbertsllms.txtRyanAlberts/best-of-Agent-Harnesses/llms.txt
# Best of Agent Harnesses > Hand-curated, ranked list of 167 AI agent harnesses — the
A markdown file at a website's root that gives language models a short guide to the site and links to the pages worth reading.
The same idea with the content included, so an agent can read the documentation in one request.
Agents and tools that fetch documentation on someone's behalf. It's a proposal, not a standard, and support varies.
Start with a one-line summary, then sections of links with a sentence each. The examples here show what real projects do.
