llm-runtime-architecture
Use when designing how one canonical agent core runs across Codex, Claude Code, Gemini CLI, Cursor, and AGENTS.md-compatible tools.
Profile →npx skills add agentlas-ai/Agentlas-OS --skill llm-runtime-architecture --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# 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`.
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- Output
What does the llm-runtime-architecture skill do?
Use when designing how one canonical agent core runs across Codex, Claude Code, Gemini CLI, Cursor, and AGENTS.md-compatible tools.
How do I install it?
Run `npx skills add agentlas-ai/Agentlas-OS --skill llm-runtime-architecture --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From agentlas-ai/Agentlas-OS, a repository with 1,165 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.