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adk-architecture

Explains how the ADK runtime fits together: the node and graph execution model, Context and Event flow, checkpoint and resume, tracing, and the rules governing the public API surface. Use when answering "how does X work" about ADK internals, tracing where an event or a piece of state comes from, deciding where a new capability belongs, reviewing a change to BaseNode, Workflow, Runner, Agent, Event or Context, working out why a node re-ran or stayed waiting after a resume, or judging whether a change breaks the public API. Don't use for assembling an agent from existing pieces (use adk-agent-builder), diagnosing one failing run or test (use adk-debug), or formatting and naming conventions (use adk-style).

DeepseekModel キュレーション済みスキル 品質 優秀 · 90 v1.0.0

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https://deepseekmodel.com/api/download.php?id=google-adk-python-agents-skills-adk-architecture-skill-md&format=skill
ダウンロード .skill 標準形式。system_prompt と model_config を収録し、任意の Agent で利用可能
.skill ファイルの system_prompt フィールドの実際の内容。
name adk-architecture description Explains how the ADK runtime fits together: the node and graph execution model, Context and Event flow, checkpoint and resume, tracing, and the rules governing the public API surface. Use when answering "how does X work" about ADK internals, tracing where an event or a piece of state comes from, deciding where a new capability belongs, reviewing a change to BaseNode, Workflow, Runner, Agent, Event or Context, working out why a node re-ran or stayed waiting after a resume, or judging whether a change breaks the public API. Don't use for assembling an agent from existing pieces (use adk-agent-builder), diagnosing one failing run or test (use adk-debug), or formatting and naming conventions (use adk-style). ADK Architecture The runtime is a graph of nodes. BaseNode is the unit of execution. Workflow is a node that schedules other nodes along declared edges. NodeRunner executes exactly one node. Runner owns the invocation and the session. Agents are nodes too — BaseAgent extends BaseNode . A node communicates with its parent through a per-execution Context , and with the session through Event s it yields. Those are two separate channels: ctx carries the result upward, events carry persistence and streaming. Read the source before relying on any signature here. These notes drift; the code does not. Paths below are relative to src/google/adk/ . Pick a reference Question Reference What must a node implement? What may it yield? Which config fields exist? BaseNode How does the graph schedule nodes, dedup dynamic children, propagate interrupts? Workflow How does a caller start an invocation? Runner What is Agent , and which methods do I call on it? Agent I am subclassing an agent — what do I override? BaseAgent What is on an Event , and what may I assume about its lifetime? Event What does a node read and write on ctx ? Context Who creates the child Context, stamps events, retries, catches errors? NodeRunner Why are Runner, NodeRunner and Workflow three separate things? Runner roles How does a human-in-the-loop pause and resume work for one node? Checkpoint and resume How does a whole workflow survive a pause, and what does is_resumable change? Workflow resumability How are spans created, and what attributes do they carry? Observability Why does the model not see the raw event log? LLM context orchestration Is this change a breaking change? Where does a new export belong? API principles Where the code lives Concept Module BaseNode , START workflow/_base_node.py Workflow , _LoopState workflow/_workflow.py Graph , edge compilation workflow/_graph.py NodeRunner workflow/_node_runner.py DynamicNodeScheduler workflow/_dynamic_node_scheduler.py ReplayManager (resume scan) workflow/utils/_replay_manager.py NodeInterruptedError , NodeTimeoutError workflow/_errors.py Context , ctx.run_node() agents/context.py ReadonlyContext agents/readonly_context.py InvocationContext agents/invocation_context.py BaseAgent , LlmAgent (aliased Agent ) agents/base_agent.py , agents/llm_agent.py Event , NodeInfo events/event.py EventActions events/event_actions.py Branch paths ( parent.child@1 ) events/_branch_path.py Node paths ( wf@1/child@2 ) events/_node_path_builder.py Runner , InMemoryRunner runners.py LiveRequestQueue , LiveRequest live/live_request_queue.py Node spans, TelemetryContext telemetry/node_tracing.py ResumabilityConfig apps/_configs.py Everything under workflow/ is a leading-underscore module. Treat those names as internal — they can change without a major version bump, so a change there is not automatically a breaking change.
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ダウンロードした .skill に含まれるフィールド。
フィールド 説明
formatフォーマット識別子(skill/v1)
skill_idスキル固有 ID
nameスキル名
versionバージョン
description説明
categoryカテゴリ(配列)
trigger_wordsトリガーワード
tagsタグ
sourceソース
source_urlソース URL(本ページ)
exported_atエクスポート日時(ダウンロード毎)
system_promptシステムプロンプト本文
model_configモデル設定:provider / model / temperature / max_tokens / top_p
examplesサンプル
install_guide各プラットフォームの導入説明(Coze / Dify / Claude / カスタム)
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.skill 標準形式。system_prompt と model_config を収録し、任意の Agent で利用可能 ダウンロード
.skillpro 拡張形式。scripts / tools / dependencies / hooks を含む ダウンロード
.json 純粋な JSON 出力。system_prompt とモデル設定のみ ダウンロード
Coze frontmatter 付き Markdown。Coze へのインポート用 ダウンロード
Dify Dify DSL。アプリ作成後にそのままインポート ダウンロード

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