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Main Agent spawns Subagents like a hen with her chicks ๐Ÿ”๐Ÿชบ๐Ÿฆ

Overview

Main Agent spawns Subagents like a hen with her chicks ๐Ÿ”๐Ÿชบ๐Ÿฆ

README


Overview

%%{init: {'theme': 'base', 'themeVariables': { 'primaryColor': '#8b5cf6', 'primaryTextColor': '#fff', 'primaryBorderColor': '#7c3aed', 'lineColor': '#a78bfa', 'secondaryColor': '#ec4899', 'tertiaryColor': '#6366f1', 'noteTextColor': '#fff', 'noteBkgColor': '#8b5cf6', 'textColor': '#fff' }}}%%
mindmap
  root((๐Ÿ” Agentic Systems))
    ๐Ÿฆ„ Foundations
      Augmented LLM
      What Changed 2026
    โš™๏ธ Workflows
      ๐ŸŽ๏ธ Baseline
      โ›“๏ธ Chaining
      ๐Ÿšฆ Routing
      ๐Ÿ›ค๏ธ Parallel
      ๐Ÿฆ‘ Orchestrator
      ๐Ÿฉป Evaluator
    ๐Ÿ” Autonomous Agent
      The Alternative
      Multi-Window
    ๐Ÿ› ๏ธ Implementation
      ๐Ÿฆ Subagent
      ๐Ÿฆด Command
      ๐Ÿ“š Skill
      ๐Ÿช Hook
    ๐Ÿ“œ Patterns as Code
      Check before
      Trace after

[!TIP] New in the 2026 edition โ€” ๐Ÿ—ž๏ธ What Changed 2025-2026 (the dated map: context engineering, the multi-agent debate, the AGENTS.md ยท SKILL.md ยท MCP stack, harness engineering) and ๐Ÿ“œ Patterns as Code (every pattern as a runnable file โ€” checked in CI on every push, no API key needed).

โฌ†๏ธ real capture: a repeated prompt graduates into a checked, runnable file โ€” every pattern in this repo works this way ยท and three of them run a real campaign daily ๐Ÿ›ฐ๏ธ

๐Ÿ—บ๏ธ Navigation


Quick Decision

%%{init: {'theme': 'base', 'themeVariables': {'lineColor': '#64748b'}}}%%
flowchart LR
    START((๐ŸŽฏ Task)) --> DEST{Destructive?}
    DEST -->|Yes| WIZ[๐Ÿง™ Wizard]
    DEST -->|No| COMP{Complex?}
    COMP -->|No| BASE[๐ŸŽ๏ธ Baseline]
    COMP -->|Yes| PRED{Predictablesteps?}
    PRED -->|Yes| WORK{Needspecialists?}
    PRED -->|No| AGENT[๐Ÿ” Autonomous]
    WORK -->|No| CHAIN[โ›“๏ธ Chain]
    WORK -->|Yes| ORCH[๐Ÿฆ‘ Orchestrator]

    classDef default fill:#f8fafc,stroke:#64748b,stroke-width:1px,color:#1e293b
    classDef decision fill:#fef3c7,stroke:#f59e0b,stroke-width:2px,color:#92400e
    classDef baseline fill:#64748b,stroke:#475569,stroke-width:2px,color:#ffffff
    classDef wizard fill:#14b8a6,stroke:#0d9488,stroke-width:2px,color:#ffffff
    classDef workflow fill:#8b5cf6,stroke:#7c3aed,stroke-width:2px,color:#ffffff
    classDef agent fill:#ec4899,stroke:#db2777,stroke-width:2px,color:#ffffff

    START:::decision
    DEST:::decision
    COMP:::decision
    PRED:::decision
    WORK:::decision
    BASE:::baseline
    WIZ:::wizard
    CHAIN:::workflow
    ORCH:::workflow
    AGENT:::agent
Situation โ†’ Use
Simple task (1 step) ๐ŸŽ๏ธ Baseline
Sequential (2-4 steps) โ›“๏ธ Prompt Chaining
Categorize inputs ๐Ÿšฆ Routing
Independent subtasks ๐Ÿ›ค๏ธ Parallelization
Multiple specialists ๐Ÿฆ‘ Orchestrator-Workers
Quality iteration ๐Ÿฉป Evaluator-Optimizer
Open-ended / unknown steps ๐Ÿ” Autonomous Agent
Destructive operations ๐Ÿง™ Wizard
Long-running (>10 min) ๐Ÿ–ฅ๏ธ Multi-Window Context

Anthropic Taxonomy

%%{init: {'theme': 'base', 'themeVariables': {'lineColor': '#64748b'}}}%%
flowchart LR
    subgraph WORKFLOWS["โš™๏ธ WORKFLOWS"]
        direction TB
        W1[๐ŸŽ๏ธ Baseline]
        W2[โ›“๏ธ Prompt Chaining]
        W3[๐Ÿšฆ Routing]
        W4[๐Ÿ›ค๏ธ Parallelization]
        W5[๐Ÿฆ‘ Orchestrator]
        W6[๐Ÿฉป Evaluator]
    end

    subgraph AGENTS["๐Ÿ” AUTONOMOUS AGENT"]
        direction TB
        A1[๐Ÿ” The Alternative]
        A2[๐Ÿ–ฅ๏ธ Multi-Window variant]
    end

    CODE[๐Ÿ“ Code controls] --> WORKFLOWS
    WORKFLOWS --> LLM[๐Ÿง  LLM controls]
    LLM --> AGENTS

    classDef workflowBox fill:#ede9fe,stroke:#8b5cf6,stroke-width:2px,color:#5b21b6
    classDef agentBox fill:#fce7f3,stroke:#ec4899,stroke-width:2px,color:#9d174d
    classDef control fill:#f1f5f9,stroke:#64748b,stroke-width:1px,color:#475569

    WORKFLOWS:::workflowBox
    AGENTS:::agentBox
    CODE:::control
    LLM:::control

Key distinction: Workflows have predefined paths (code controls). Agents decide their own path (LLM controls).


Critical Rule

%%{init: {'theme': 'base', 'themeVariables': {'lineColor': '#64748b'}}}%%
flowchart LR
    U1[๐Ÿ™‹โ€โ™€๏ธ User] -->|request| MA[๐Ÿ” Main Agent]
    MA -->|๐Ÿชบ spawn| SA1[๐Ÿฆ Subagent]
    MA -->|๐Ÿชบ spawn| SA2[๐Ÿฆ Subagent]
    SA1 -->|result| MA
    SA2 -->|result| MA
    MA -->|response| U2[๐Ÿ’โ€โ™€๏ธ User]

    SA1 x--x|"โŒ CANNOT spawn"| SA3[๐Ÿฆ]

    classDef user fill:#6366f1,stroke:#4f46e5,stroke-width:2px,color:#ffffff
    classDef main fill:#f59e0b,stroke:#d97706,stroke-width:2px,color:#ffffff
    classDef sub fill:#ec4899,stroke:#db2777,stroke-width:2px,color:#ffffff
    classDef blocked fill:#ef4444,stroke:#dc2626,stroke-width:2px,color:#ffffff,stroke-dasharray: 5 5

    U1:::user
    U2:::user
    MA:::main
    SA1:::sub
    SA2:::sub
    SA3:::blocked

๐Ÿฆ Subagents cannot spawn other ๐Ÿฆ subagents. All delegation flows through ๐Ÿ” Main Agent.


Repository Structure

.
โ”œโ”€โ”€ README.md                      # ๐Ÿ  You are here
โ”‚
โ”œโ”€โ”€ foundations/                   # ๐Ÿฆ„ Core concepts
โ”‚   โ””โ”€โ”€ augmented-llm.md
โ”‚
โ”œโ”€โ”€ workflows/                     # โš™๏ธ Predefined orchestration
โ”‚   โ”œโ”€โ”€ 00-baseline.md
โ”‚   โ”œโ”€โ”€ 01-prompt-chaining.md
โ”‚   โ”œโ”€โ”€ 02-routing.md
โ”‚   โ”œโ”€โ”€ 03-parallelization.md
โ”‚   โ”œโ”€โ”€ 04-orchestrator-workers.md
โ”‚   โ””โ”€โ”€ 05-evaluator-optimizer.md
โ”‚
โ”œโ”€โ”€ agents/                        # ๐Ÿ” Autonomous Agent (the alternative)
โ”‚   โ”œโ”€โ”€ autonomous.md              # The pattern
โ”‚   โ””โ”€โ”€ multi-window.md            # Variant
โ”‚
โ”œโ”€โ”€ implementation/                # ๐Ÿ› ๏ธ Claude Code specifics
โ”‚   โ”œโ”€โ”€ components/                # ๐Ÿฆ๐Ÿฆด๐Ÿ“š๐Ÿช
โ”‚   โ””โ”€โ”€ architecture/              # 5-layer system
โ”‚
โ”œโ”€โ”€ guides/                        # ๐Ÿ—บ๏ธ Selection & use cases
โ”‚   โ””โ”€โ”€ use-cases/                 # 6 validated examples
โ”‚
โ””โ”€โ”€ reference/                     # ๐Ÿ“– Glossary, standards

References

Resource Link
Building Effective Agents anthropic.com/engineering
Claude Code Docs docs.anthropic.com
Agent SDK docs.anthropic.com/agent-sdk
Anthropic Cookbook github.com/anthropics
Agent Skills spec agentskills.io
Agentic AI Foundation (MCP ยท AGENTS.md ยท goose) aaif.io
Patterns as runnable files (this repo) patterns-as-code/

Contributing

Contributions welcome! See CONTRIBUTING.md.

Requirements: Official sources โ€ข Code examples โ€ข Mermaid diagrams โ€ข Established format


View this README on GitHub

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