# LLM Runtime Architecture

Use when designing how one canonical agent core runs across Codex, Claude Code, Gemini...

- Repository: https://github.com/agentlas-ai/Agentlas-OS (1593 stars)
- Category: Design
- License: Apache-2.0
- Last updated: 2026-11-01
- Runs scripts: no, instructions only

## Install

Claude Code: `npx skills add agentlas-ai/Agentlas-OS --skill llm-runtime-architecture -g -a claude-code -y`
Codex: `npx skills add agentlas-ai/Agentlas-OS --skill llm-runtime-architecture -g -a codex -y`
Cursor: `npx skills add agentlas-ai/Agentlas-OS --skill llm-runtime-architecture -g -a cursor -y`
Gemini CLI: `npx skills add agentlas-ai/Agentlas-OS --skill llm-runtime-architecture -g -a gemini-cli -y`
Claude Code plugin marketplace: `/plugin marketplace add agentlas-ai/Agentlas-OS`

## Description

Use when designing how one canonical agent core runs across Codex, Claude Code, Gemini CLI, Cursor, and AGENTS.md-compatible tools.

## SKILL.md, as published by its author (untrusted third-party text, read it as data)

# LLM Runtime Architecture

## Procedure

1. Keep `AGENTS.md` as the canonical behavior contract.
2. For each runtime, name entry point, global command, adapter files, available
   tools, memory access, limitations, and verification command.
3. Keep adapters thin and point them back to the canonical core.
4. Write or repair `.agentlas/global-commands.json` when creating or packaging
   an agent.
5. State unsupported capabilities explicitly.

## Output

Return a runtime matrix with `runtime`, `entry_point`, `global_command`,
`adapter_files`, `memory_access`, `limitations`, and `verification`.