Setup

Start Hermes from the workspace root that contains the markdown you want Enzyme to index. The Enzyme CLI owns local indexing and refresh; Hermes uses the installed skill to know when to call it.

Install the CLI, then run enzyme install hermes from the workspace root before starting Hermes.

Ask Hermes to set up Enzyme for the workspace. It should preserve the existing markdown structure and show you when memory is ready to use.

Existing Obsidian conventions matter: inbox folders, daily notes, people/contact pages, tags, wikilinks, and date frontmatter are retrieval signal. Enzyme can propose frontmatter or people-page backfills, but it should show the exact files before changing them.

See Hermes Agent + Enzyme for the exact flow.

Enzyme builds a local semantic graph for your markdown and exposes a CLI to efficiently query it for context. At setup time, it interprets the structure of your workspace and persists this to a configuration that you can modify.

See Data flow & trust for reset/uninstall details and provider boundaries, and Supported runtimes for the runtime matrix.

Use exact search, grep, or Obsidian search when you know the name, date, tag, filename, or phrase. Use a plain vector/RAG tool when you only need semantic passage search over mostly unstructured documents. Use a managed memory API if your first need is a hosted backend for app-user memories.

Enzyme is strongest when your markdown has enough prose and handles — folders, tags, wikilinks, dates, frontmatter, project notes, meeting notes, or decision logs — for an agent to prep from source-grounded context.

By default, enzyme init and enzyme refresh use Enzyme hosted credits/auth for catalyst generation. They ignore inherited OPENAI_* and OPENROUTER_* env vars so an existing personal key is not used accidentally.

Bring your own OpenAI/OpenRouter/OpenAI-compatible provider only when you intend to bill through that provider: set the env vars and run enzyme init --use-env-llm or enzyme refresh --use-env-llm.

Query-time retrieval from the compiled index is local. The provider/credit path is for generating catalysts during init or refresh.

During enzyme init or enzyme refresh, selected excerpts are sent to an LLM for catalyst generation. Your raw files stay on your device. Nothing is stored on Enzyme's servers.

The default path uses Enzyme hosted credits/auth and ignores inherited personal LLM env keys. If you explicitly pass --use-env-llm with your own API key, excerpts go directly to the provider you configure. Hosted-credit excerpts are sent to OpenRouter (a US-based model provider). Enzyme does not store your raw files or log your note content. See privacy for details.

Set OPENAI_API_KEY or OPENROUTER_API_KEY to use your own provider, then pass --use-env-llm on enzyme init or enzyme refresh. Base URL and model overrides are optional; if you only set model/base without a key, that is an incomplete env-provider config.

For local servers (LM Studio, Ollama, vLLM) that don't require authentication, use a placeholder key:

When your env provider is active, enzyme init --use-env-llm prints the resolved model, base URL, and a masked key so you can confirm it's using your provider. Without --use-env-llm, Enzyme stays on hosted credits/auth even if those env vars exist.

Provider compatibility: Enzyme uses the OpenAI chat completions format. Most providers work out of the box. Tested providers include OpenRouter, OpenAI-compatible endpoints, Azure OpenAI, Together AI, Groq, LM Studio, Ollama, and vLLM.