v1.0.35 Release

OpenClaw Swarms.

OpenClaw is the high-performance agent orchestration engine at the core of MeltyBase. It is designed for multi-agent coordination, parallel tool execution, and long-term semantic memory retention.

01. Agent Orchestration Engine

The OpenClaw engine operates on a loop-based reasoning cycle. Every agent interaction is enriched with real-time context and session history before execution.

MaxTurns Depth

Agents default to a 3-turn reasoning loop, allowing them to verify tool outputs and correct errors before returning a final answer.

Parallel Execution

Batch 177 update enables agents to trigger multiple tool calls simultaneously, drastically reducing latency for complex workflows.

Semantic Caching

Uses cosine distance (0.95 threshold) to match incoming prompts against a vector cache, saving compute cycles on repetitive queries.

02. Swarm Coordination

OpenClaw Swarms enable multiple specialized agents to collaborate on a single master objective. Coordination is handled by the SwarmService.

                    // Inter-Swarm Coordination Logic
                    type SwarmStatus struct {
                        ProjectID       uuid.UUID
                        SwarmID         string
                        MasterObjective string
                        AgentCount      int
                        Health          string
                    }
                

Peer Discovery: Swarms can discover and sync context with peer swarms across different project boundaries.
Leadership Election: Dynamic selection of a "Leader Agent" to delegate sub-tasks to specialized workers.
Persona Migration: Securely package and transfer agent personas and memories between projects while respecting owner boundaries.

03. Semantic Memory Mesh

MeltyBase provides agents with a dual-layer memory system. This ensures that agents learn from every interaction while maintaining high-speed recall.

Episodic Memory

Captures the last 10 exchanges within a session for immediate conversational continuity.

Vector Long-Term

Interactions are embedded and stored in a vector partition, allowing agents to recall relevant facts months later.

04. Security & Isolation

OpenClaw is built for the "Owner-Operated" model, where privacy is non-negotiable.

Mandatory PII Masking: Every query is scrubbed of Personally Identifiable Information before being processed by the LLM.
Sentinel Guardrails: Fine-grained permission control over which agents are allowed to access specific tools or APIs.
Context Isolation: Agent memories are strictly partitioned by project, preventing cross-tenant data leakage.