Multi-Agent Runs
Run multiple agents in parallel with knowledge sharing.
CORAL's multi-agent mode lets several agents work on the same task simultaneously, sharing discoveries through notes and skills.
Configuration
agents:
count: 4 # Spawn 4 agents
model: sonnet # All use the same modelOr override at launch:
coral start -c task.yaml --agents 4How agents collaborate
Shared attempts
All agents can see each other's eval scores and diffs. When agent-2 achieves a high score, agent-1 can inspect that attempt:
# From inside an agent's worktree:
coral log # See all attempts from all agents
coral show <commit-hash> # See the diff of a specific attemptNotes
Agents write Markdown notes to share insights:
coral notes # List all notes
coral notes --read 3 # Read a specific noteNotes are stored in .coral/public/notes/ and visible to all agents.
Skills
Agents can package reusable tools as skills — directories with a SKILL.md and associated files:
coral skills # List all skills
coral skills --read profiler # Show skill detailsKnowledge sharing patterns
Consolidation heartbeat
The default consolidate heartbeat (every 10 global evals) prompts agents to write notes about their findings. This creates a shared knowledge base that new iterations can draw from.
agents:
heartbeat:
- name: consolidate
every: 10
global: true # Triggers based on total evals across all agentsReading sibling worktrees
Agents can read (but not write to) other agents' worktrees. This lets them inspect successful approaches directly:
agent-1/ → can read agent-2/solution.py
agent-2/ → can read agent-1/solution.pyMonitoring multi-agent runs
CLI
coral status # Agent health overview
coral log # Leaderboard across all agents
coral log --agent agent-1 # Filter by agentWeb dashboard
coral uiThe dashboard shows:
- Real-time score chart with per-agent lines
- Agent status indicators (active, idle, stopped)
- Attempt history with agent filtering
- Notes and skills browsers
- Live agent logs