Learn Claude Code

Learn Claude Code

0 から 1 へ nano Claude Code-like agent を構築し、毎回 1 つの仕組みを追加

コアパターン

すべての AI コーディングエージェントは同じループを共有する:モデルを呼び出し、ツールを実行し、結果を返す。実運用ではこの上にポリシー、権限、ライフサイクル層が重なる。

agent_loop.py
while True:
    response = client.messages.create(messages=messages, tools=tools)
    if response.stop_reason != "tool_use":
        break
    for tool_call in response.content:
        result = execute_tool(tool_call.name, tool_call.input)
        messages.append(result)

メッセージの増加

エージェントループ実行時のメッセージ配列の成長を観察

messages[]len=0
[]

学習パス

20の段階的セッション、シンプルなループから完全なマルチエージェント Harness まで

s01102 行

The Agent Loop

The smallest useful agent is a loop that calls the model, runs tools, and feeds results back.

s02135 行

Tool Use

The loop stays stable while capabilities register into a dispatch table.

s03180 行

Permission

Dangerous actions need a harness decision point before the shell runs.

s04232 行

Hooks

Cross-cutting behavior belongs around the loop, not tangled inside it.

s05236 行

TodoWrite

Explicit plans keep long-running work visible and correctable.

s06304 行

Subagent

Subagents give each subtask a clean message history while preserving the main thread.

s07335 行

Skill Loading

Inject specialized knowledge only when the task actually needs it.

s08414 行

Context Compact

Compression keeps the conversation usable when the context window gets crowded.

s09528 行

Memory

Some facts should survive summarization and future sessions.

s10166 行

System Prompt

The system prompt is a generated product of policy, tools, skills, and context.

s11287 行

Error Recovery

A robust harness classifies failures and decides what kind of retry is worthwhile.

s12297 行

Task System

A task graph turns vague goals into ordered, observable work.

s13379 行

Background Tasks

The agent can keep reasoning while slow work completes elsewhere.

s14645 行

Cron Scheduler

Recurring work should be created by the harness, not remembered by the model.

s15745 行

Agent Teams

Persistent teammates let work continue in parallel without stuffing every thought into one context.

s16709 行

Team Protocols

Multi-agent systems need explicit message contracts, not vibes.

s17648 行

Autonomous Agents

Teammates become useful when they can discover and claim work themselves.

s18802 行

Worktree Isolation

Parallel agents need isolated filesystems as much as isolated conversations.

s19835 行

MCP Tools

External services can become agent tools through a standard discovery and call protocol.

s201708 行

Comprehensive Agent

The final harness is still one loop, now surrounded by the systems that make it production-shaped.

アーキテクチャ層

5つの直交する関心事が完全なエージェントを構成