Multi-Agent Memory
Patterns for sharing and isolating memory across multiple AI agents using ClawVault.
Multi-Agent Memory
When multiple agents operate in the same environment, memory management becomes a coordination problem. ClawVault supports both shared vaults (agents read and write the same memory) and isolated vaults (each agent has its own memory space).
Shared Vaults vs Isolated Vaults
Shared Vault
All agents read and write to the same vault directory. Best for agents that collaborate on the same tasks and need unified context.
Pros: Single source of truth, no sync overhead, full cross-agent visibility.
Cons: Risk of conflicting writes, noisy observations, harder to attribute memories.
Isolated Vaults
Each agent has its own vault. Cross-agent context is exchanged explicitly. Best for agents with distinct responsibilities.
Pros: Clean separation, no write conflicts, agent-specific tuning.
Cons: Requires explicit context sharing, potential for knowledge silos.
When to Share
Share a vault when agents:
- Work on the same project and need each other's decisions
- Operate sequentially (one agent hands off to another)
- Have non-overlapping categories (one stores decisions, another stores observations)
When to Isolate
Use separate vaults when agents:
- Serve different users or contexts
- Have conflicting observation schedules
- Need different LLM configurations for compression
- Operate in parallel on unrelated tasks
Agent-Specific Memory Folders
Within a shared vault, you can partition by agent using category prefixes or dedicated folders:
vault/
.clawvault.json
decisions/ # shared
projects/ # shared
agents/
agent-alpha/ # agent-specific observations
agent-beta/ # agent-specific observations
inbox/
agent-alpha/ # agent-specific captures
agent-beta/Each agent stores its observations and quick captures in its own subfolder while sharing access to decisions, projects, and other cross-cutting categories.
Configure per-agent paths in each agent's environment:
# Agent Alpha
export CLAWVAULT_AGENT_ID="agent-alpha"
# Agent Beta
export CLAWVAULT_AGENT_ID="agent-beta"ClawVault uses CLAWVAULT_AGENT_ID to namespace observations and captures when set.
Cross-Agent Context
The clawvault context command generates task-relevant context from the vault. In a multi-agent setup, any agent can query the shared vault:
# Agent Beta needs context about a decision Agent Alpha made
clawvault context "authentication architecture decision"This returns relevant memories regardless of which agent created them, because context searches across all vault categories.
Explicit Context Passing
For isolated vaults, use clawvault sync to share specific categories:
# Export decisions from Agent Alpha's vault to a shared location
clawvault sync /shared/decisions --categories decisions
# Agent Beta imports from the shared location
clawvault sync /shared/decisions --into /agent-beta/vault/shared-decisionsPatterns for Agent Orchestration
Hub-and-Spoke
A coordinator agent maintains the shared vault. Worker agents have isolated vaults but push summaries to the hub:
┌─────────────┐
│ Coordinator │
│ (hub) │
└──────┬──────┘
│ shared vault
┌──────────┼──────────┐
│ │ │
┌─────┴──┐ ┌────┴───┐ ┌───┴─────┐
│Worker A│ │Worker B│ │Worker C │
│(isolat)│ │(isolat)│ │(isolat) │
└────────┘ └────────┘ └─────────┘Workers run clawvault sleep with summaries that the coordinator observes.
Pipeline
Agents operate sequentially. Each agent's sleep handoff becomes the next agent's wake input:
# Agent 1 finishes
clawvault sleep "research complete" --next "write draft based on findings"
# Agent 2 starts
clawvault wake # picks up Agent 1's handoffParallel with Merge
Multiple agents work independently, then a merge agent consolidates:
# After parallel agents finish, merge agent runs:
clawvault observe --compress # processes all new transcripts
clawvault link --all # resolves cross-references
clawvault graph # shows the unified pictureMulti-agent patterns are evolving. The CLAWVAULT_AGENT_ID environment variable and per-agent namespacing are the current recommended approach. Future versions may add first-class multi-agent coordination commands.