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AI Assistant Integration Resources

Aembit supports the llms.txt convention for Large Language Models (LLM) to learn about Aembit. This standard provides a way for LLMs to understand the capabilities and features of Aembit, as well as how to interact with it.

Using these resources with AI assistants

Section titled “Using these resources with AI assistants”

Feed these resources to AI coding assistants (Claude, GitHub Copilot, ChatGPT) when you need help implementing Aembit integrations.

Example workflows:

  • Generating API integration code: Provide api-cloud-endpoints.txt or api-edge-endpoints.txt when asking your LLM to generate API client code
  • Understanding configuration options: Use llms-full.txt when asking questions about Aembit features, concepts, and configuration patterns
  • Troubleshooting: Provide relevant resource to your LLM along with error messages for context-aware debugging suggestions

Main documentation

Section titled “Main documentation”

Core Aembit documentation including Get Started Guide, User Guide, CLI Guide, and support information. All variants cover workload identity concepts, Client Workload configuration, Access Policies, Trust Providers, and Credential Providers.

  • llms.txt - List of available files and directories in the main Aembit docs
  • llms-small.txt - Condensed main documentation (optimized context, fastest loading)
  • llms-full.txt - Complete main documentation including advanced configuration and examples (comprehensive)

Aembit Cloud API

Section titled “Aembit Cloud API”

Complete API reference for the Aembit Cloud API, separated into focused resources for efficient token usage. Covers API endpoints, authentication, access management, policy configuration, and credential provider operations.

Aembit Edge API

Section titled “Aembit Edge API”

Complete API reference for the Aembit Edge API, separated into focused resources for efficient token usage. Covers Edge deployment, Kubernetes integration, local authentication, and workload identity verification.