Satori CLI Integration

Satori persists notable information across AI applications. It stores facts in both vector and knowledge graph databases for later retrieval.

Environment Requirements

Works in: Claude Code, Cursor, Windsurf, or any AI tool with local terminal access.

Authentication

The CLI auto-configures on first run:

• Checks ~/.config/satori/satori.json for API key and memory ID
• If missing, creates the file and provisions new credentials automatically
• No manual setup required

CLI Commands

Save facts:

npx -y @satori-sh/cli@latest add "<facts>"

Search for context:

npx -y @satori-sh/cli@latest search "<query>"

Workflow: Proactive Search

At conversation start, if the user's message suggests existing context would help:

1. Extract key entities/topics from user's first message
2. Run search command with relevant query
3. Parse JSON response to extract relevant facts
4. Silently incorporate retrieved context into response
5. Do NOT announce "I searched Satori" unless results significantly impact the response

Parsing search results: The CLI returns JSON. Extract the relevant facts and use them as context:

npx -y @satori-sh/cli search "Flamingo project tech stack"
# Returns JSON with matching facts - parse and incorporate naturally

Example triggers for proactive search:

• "Let's continue working on [project]"
• "What's the status of [thing]"
• References to past decisions without full context
• Project names, company names, people names

Workflow: Save Facts

When to Save

Save at natural breakpoints:

• End of a decision-making discussion
• When user explicitly requests ("remember this", "save this")
• After establishing concrete preferences, names, dates, deadlines
• When significant project context is established

What to Save

See references/fact-criteria.md for detailed criteria.

SAVE - Notable, persistent information:

• Decisions: "Using PostgreSQL for the database"
• Tech preferences: "User prefers Bun over Node"
• Names/branding: "Company name is Flamingo, they make pink cookies"
• Dates/deadlines: "MVP deadline is March 15"
• Architecture choices: "Microservices with event sourcing"
• Strategic directions: "Targeting enterprise customers first"
• Key contacts: "Sarah is the design lead"
• Project context: "Satori is an AI memory infrastructure company"

DO NOT SAVE - Transient, granular, or obvious:

• Work-in-progress feedback: "the color scheme needs work"
• Claude's explanations or code snippets
• Temporary debugging context
• Generic preferences derivable from context
• Conversational filler

Save Execution

1. Extract notable facts from conversation (see criteria)
2. Format as natural language, batch related facts together
3. Execute CLI command
4. On success: continue silently (fire-and-forget)
5. On failure: notify user with error