Understand how OPC coordinates multiple Claude Code processes through event hooks, skills, scripts, files, and a database. It explains child-agent startup, process tracking, output storage, and completion reporting, helping readers follow the system's architecture.
OPC Architecture Understanding
Review the instructions the agent will receive before you install.
OPC (Orchestrated Parallel Claude) extends Claude Code - it does NOT replace it.
Claude Code CLI is the execution engine. OPC adds orchestration via:
When you spawn an agent:
subprocess.Popen(["claude", "-p", "prompt"])$ claude ← Main Claude Code (your terminal)
↓ Task tool triggers hook
↓ subprocess.Popen(["claude", "-p", "..."])
├── claude -p "research..." ← Child agent 1
├── claude -p "implement..." ← Child agent 2
└── claude -p "test..." ← Child agent 3
.claude/hooks/.claude/skills/.claude/
├── hooks/ ← TypeScript hooks that Claude Code runs
├── skills/ ← SKILL.md prompts that Claude Code loads
├── settings.json ← Hook registration, Claude Code reads this
└── cache/ ← State files, agent outputs
opc/
├── scripts/ ← Python scripts called by hooks
├── docker-compose.yml ← PostgreSQL, Redis, PgBouncer
└── init-db.sql ← Database schema
claude in terminal.claude/settings.jsonclaude -p "research..." as subprocess.claude/cache/agents/<id>/claude -p processNo reviews yet. Tell others what you thought.
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Coordinate background agents through saved files, keeping lengthy work transcripts out of the main conversation. It defines how to pass results between agents, monitor progress, and verify completed work with tests.
Delegate implementation, file reading, and testing to separate agents, then bring concise summaries back to the main conversation. The rules explain when delegation helps and when a small edit is better handled directly.
Organize implementation work across research, planning, validation, implementation, and review agents. Each stage passes files to the next, while implementation starts with failing tests and the main conversation coordinates the workflow.
Connect Agentica SDK agents to Claude Code CLI through a proxy, an intermediary server. Use setup and debugging guidance to address file permissions, streamed responses, result formatting, and agents reporting success without performing the requested operations.
Consult Agentica APIs when building workflows where multiple AI agents cooperate. This reference covers eleven coordination patterns, agent tracking, shared state, handoffs, and ways to combine results, with pointers to detailed API specifications.
Write clearer instructions for Agentica and REPL agents by specifying roles, file operations, and output formats. Includes templates for dividing research, coordinating specialists, reviewing solutions, and passing results between agents through files.