Session Context Bridge

Stop reinventing context between sessions. Stop losing learnings when subagents complete. Stop treating parallel tasks as isolated black boxes.

Session Context Bridge bridges isolated OpenClaw sessions via file-based IPC. Handoffs. Results harvesting. Regression propagation. All the machinery of real multi-agent teams, working out of the box.

What You Get

✅ Handoff Files — Pass context to subagents before they spawn. Goal, constraints, previous friction. Subagents inherit your knowledge instead of rediscovering.

✅ Results Harvesting — After subagents complete, extract learnings automatically. Structured findings, key insights, failure modes to prevent.

✅ Regression Propagation — When a subagent discovers a mistake, add it to shared guardrails. All future sessions load those rules on boot. Never repeat the same error.

✅ Parallel Execution — Run 3, 5, 10 subagents in parallel. No race conditions. Independent session directories. Harvest results when all complete.

✅ Memory Integration — Learnings flow back to MEMORY.md automatically. Future sessions remember what past sessions discovered.

Real Example

Main session writes handoff with goal, context, constraints. Subagent spawns, loads handoff, skips rediscovery. Researches 7 payment providers. Writes findings.

Parent harvests: findings, learnings, regressions flow to MEMORY.md. Next subagent already knows the blockers.

Who This Is For

• AI founders running autonomous companies
• AI teams coordinating multi-agent workflows
• Researchers running parallel analysis tasks
• Anyone with subagents who want them to learn from each other

What's Included

• Complete SKILL.md specification (ready to integrate)
• Python tools: handoff.py (write/load), results.py (harvest/propagate)
• Integration guide + test script
• Real test results (crypto research + pricing analysis included)
• Tested extensively with real subagents. All tests passing. Production-ready.