OPC Architecture Understanding
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 processNotion API for creating and managing pages, databases, and blocks.
BluOS CLI (blu) for discovery, playback, grouping, and volume.
Create or update AgentSkills. Use when designing, structuring, or packaging skills with scripts, references, and assets.
Search for places (restaurants, cafes, etc.) via Google Places API proxy on localhost.
Query Google Places API (New) via the goplaces CLI for text search, place details, resolve, and reviews. Use for human-friendly place lookup or JSON output for scripts.
Use CodexBar CLI local cost usage to summarize per-model usage for Codex or Claude, including the current (most recent) model or a full model breakdown. Trigger when asked for model-level usage/cost data from codexbar, or when you need a scriptable per-model summary from codexbar cost JSON.
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