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Claude as intelligent orchestrator for multi-agent workflows. Coordinates specialized agents (Gemini, local models, tools) using Shell-As-Bus pattern with capability-based delegation.

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SKILL.md

name orchestrator
description Claude as intelligent orchestrator for multi-agent workflows. Coordinates specialized agents (Gemini, local models, tools) using Shell-As-Bus pattern with capability-based delegation.
version 1.1.0

Orchestrator - Multi-Agent Coordination

Claude orchestrates specialized agents to solve complex tasks efficiently.

Core Principle

"Shell-As-Bus": Every agent is a CLI tool. Bash is the universal communication bus. Files and stdout for data exchange.

Workflow

  1. Analyze request (Planning Mode):

    • Break down into sub-tasks
    • Identify required capabilities
    • Match tasks to agents via Decision Matrix
    • Check quota constraints (PROVIDER-LIMITS.md)
  2. Create execution plan:

    • Sequential for dependent tasks
    • Parallel for independent tasks
    • Hybrid for complex workflows
  3. Delegate intelligently:

    Decision Matrix:
      High Creativity/Reasoning → Execute directly (Claude)
      Massive Context (>200k tokens) → gemini-specialist
      Bulk/Repetitive Processing → local-model
      Real-time Information → gemini-specialist (Search grounding)
      Sensitive/Private Data → local-model
    
  4. Monitor execution:

    • Check agent outputs (stdout, exit codes)
    • Validate against expectations
    • Intervene on errors (fallback to Claude)
  5. Synthesize results:

    • Combine agent outputs
    • Validate consistency
    • Present unified result
  6. Handle failures (Try-Catch-Escalate):

    • Try: Delegate to specialist
    • Catch: Agent fails or produces bad output
    • Escalate: Claude fixes directly

Agent Interface Standard

All delegated agents must:

  • Be callable via CLI
  • Return clean stdout (not debug logs)
  • Use exit codes (0=success, non-zero=error)
  • Save artifacts to known paths

Good output:

Task completed. Summary: [brief]. Artifacts: [path].

Bad output:

[DEBUG] Loading...
[INFO] Processing...
[WARNING] ...

Delegation Patterns

Pattern 1: Staggered Parallel Execution (Independent Tasks)

# CRITICAL: Use staggered launch (1s delay) to avoid Gemini CLI race condition
# Workers run simultaneously AFTER startup - 4-8x faster than sequential!

TASKS=("task1" "task2" "task3" "task4")

for i in "${!TASKS[@]}"; do
  gemini -p "${TASKS[$i]}" --yolo -o text > /tmp/result$i.txt &
  sleep 1  # ← CRITICAL: Prevents concurrent startup bug (Issue #3161)
done

wait  # Wait for all to complete

# Synthesize results
for f in /tmp/result*.txt; do
  cat "$f"
done

Why staggered? Gemini CLI v0.21.1 has race condition during startup. 500ms-1s delay fixes it. Workers still run in parallel after startup!

Pattern 2: Sequential Pipeline (Dependent Tasks)

# Output of one feeds the next
gemini -p "analyze code" < code.py --yolo -o text > analysis.md
# Claude reads analysis
cat analysis.md
# Claude implements based on analysis

Pattern 3: Evaluator-Optimizer (Review Loop)

# Claude generates code
cat > draft.py << EOF
...code...
EOF

# Gemini reviews
gemini -p "security audit this code" < draft.py --yolo -o text > review.md

# Claude refines based on review
cat review.md
# Apply improvements

When to Orchestrate

Use orchestration when:

  • Task requires multiple distinct capabilities
  • Massive context exceeds Claude's window
  • Parallel execution saves time
  • Need specialized tools/search
  • Cross-validation desired

Don't orchestrate when:

  • Task is simple (single-step)
  • Only Claude's capabilities needed
  • Overhead exceeds benefit

Key Principle

Delegation > Monopolization. Use specialized agents for their strengths. Claude orchestrates and synthesizes, not does everything.


See PATTERNS.md for detailed workflows, AGENTS.md for available agent catalog, and PROVIDER-LIMITS.md for quota constraints.