Supported runtimes

Run enzyme install <target> from the markdown workspace you want the agent to use. This installs a skill to help with Enzyme setup and writes runtime instructions so the agent knows how to run the retrieval loop.

Runtime matrix

RuntimeCommandStatusWhat gets writtenHow to verify
Codex and AGENTS.md-aware agentsenzyme install codexSupportedEnzyme section in AGENTS.md; .agents/skills/enzyme/SKILL.mdStart the agent from the workspace and ask: Set up Enzyme for this vault.
Claude Codeenzyme install claudeSupportedEnzyme section in AGENTS.md; .claude/skills/enzyme/SKILL.md; CLAUDE.md import of @AGENTS.mdStart Claude Code from the workspace and ask: Set up Enzyme for this vault.
Pi / generic .agents readersenzyme install codexSupportedSame as Codex: AGENTS.md plus .agents/skills/enzyme/SKILL.mdStart Pi from the workspace and ask it to read the Enzyme skill before setup.
Hermesenzyme install hermesExperimentalWorkspace instructions plus global ~/.hermes/skills/enzyme/SKILL.mdStart Hermes from the workspace and ask it to set up Enzyme. Expect occasional integration caveats.
OpenClawenzyme install openclawExperimentalOpenClaw-compatible instructions plus global ~/.openclaw/skills/enzyme/SKILL.mdStart OpenClaw from the workspace and ask it to set up Enzyme. Expect occasional integration caveats.
CursorManual / pendingNot a dedicated install targetUse a generic AGENTS.md path only if your Cursor workflow reads those instructions.Treat as manual until a dedicated setup page exists.
Product SDKPrivate betaNot part of local runtime setupProduct-corpus integration is scoped directly with early teams.Use the SDK preview page or contact Enzyme.

If you are unsure, use:

enzyme install codex

That writes the generic .agents skill path many coding-agent workflows can read. If you use Claude Code, use enzyme install claude so Claude gets its dedicated skill path too.

What the agent should do next

After runtime install, ask the agent:

Set up Enzyme for this vault. First run a read-only scan, explain what is indexable or weakly indexable, then initialize and prove it with a project or meeting-prep query that cites source files.

A good agent-led setup should preserve your existing markdown conventions. It should not invent a new memory architecture, rewrite your vault wholesale, or write generic summaries. It should also respect provider intent: default init/refresh use Enzyme hosted credits/auth, and agents should pass --use-env-llm only when you intentionally want your own OpenAI/OpenRouter/OpenAI-compatible provider.