First successful run

A successful first run does not mean “the command exited zero.” It means your agent can prepare from your own markdown and cite the notes that matter.

Use a real project, client, research thread, or upcoming meeting. If you do not have one in mind, choose a folder or tag that has meeting notes, project notes, decisions, and open questions.

1. Let your agent set up Enzyme

Open your notes folder in an agent with terminal access and paste this:

Set up Enzyme for the Markdown notes folder I have open. If you cannot identify it, ask me for its path.

Install Enzyme if needed using https://raw.githubusercontent.com/byenzyme/enzyme/main/install.sh, and install the instructions for this agent. Read and follow the installed enzyme-workspace-setup skill.

You may use Enzyme's online service to suggest settings from my notes and prepare search. Show me what you propose to include or exclude, and let me correct it before building the local search index.

Then answer one useful question using my notes, with links to the sources, and suggest a question I can ask next. Keep my existing notes in place and unchanged. Ask separately before any cleanup, model download, or recurring task.

The agent follows the installed setup skill: propose settings with compile, review them with you, build the local index, and test an answer against real notes. You do not need to reorganize your notes first.

2. Review the proposal

Check that the agent recognizes subjects you care about and explains any folders it will leave out of search. A topic not chosen to guide search is different from an excluded folder: its notes can still be searchable.

For terminal-only setup after installing Enzyme:

enzyme compile -v
# Review the .enzyme settings file at the path printed by compile.
enzyme init --quiet
enzyme doctor
enzyme petri --query "prep for the next meeting on <project>"

compile uses online selection and saves settings. init prepares search from those settings; doctor reports what was indexed and any problems. Recognizable questions in petri are a useful starting point, but only the retrieved sources can prove an answer.

3. Run the meeting-prep test

Ask your agent:

Prep me for the next meeting on <project>. Cite the notes that show unresolved commitments, decisions, or source context.

Or run directly:

enzyme catalyze "prep for next meeting on <project> unresolved commitments decisions"

A good receipt looks like this:

$ enzyme petri
entity: [[Acme onboarding]]
catalysts:
  - what remains unresolved before the next customer check-in?
  - where did pricing language change after stakeholder pushback?

$ enzyme catalyze "prep for next Acme onboarding meeting unresolved commitments"
1. projects/acme/2026-05-12 onboarding call.md
   excerpt: "Sarah asked for revised pricing language before Friday..."
   matched catalyst: what remains unresolved before the next customer check-in?

2. decisions/acme-pricing-language.md
   excerpt: "Use implementation-risk framing; avoid calling it an enterprise tax..."
   matched catalyst: where did pricing language change after stakeholder pushback?

Pass condition

The agent should answer with:

• source file paths;
• short excerpts;
• a real unresolved commitment, decision, or project-state thread;
• a sentence explaining why the files belong together;
• an honest note when exact search is better for a specific name/date/title.

If it fails

What not to count as success

Do not count these as success:

• “Indexed N files” by itself;
• an answer that cites no source files;
• a list of filenames without excerpts;
• generic project advice;
• obvious exact matches that grep would have found faster;
• invented commitments not present in notes.

The first run should earn trust by showing the user’s own notes back to them in a useful arrangement.