adk-style

Python style and codebase conventions for ADK (Agent Development Kit): private-by-default file visibility, imports, type hints, Pydantic v2 models, formatting, docstrings, logging, async I/O, file and test layout, and unit test structure. Use when writing or editing ADK source or tests, deciding whether a new file or symbol should be public or private, naming or placing a test file, fixing a formatter, linter, or type-check failure (pyink, isort, ruff, mypy, addlicense, compliance-checks), or asking whether code matches house style. Don't use for reviewing a whole changeset (use adk-review), writing a developer guide or design doc for a code unit (use adk-unit-guide or adk-unit-design), building or configuring agents (use adk-agent-builder), or installing the toolchain (use adk-setup).

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仓库: google/adk-python
最近来源活动: 2026年10月8日 22:17
检测到的 SKILL.md 语言: 英语
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分支: 4,129

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默认使用会先检查来源的 Prompt；你也可以切换为直接命令，或下载本地副本。

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复制这段 Prompt，发给你正在使用的 AI 助手。

Follow https://skillsmp.com/skill-install/prompt.md to install only the Agent Skill at https://github.com/google/adk-python/tree/main/.agents/skills/adk-style.

直接命令不会经过审查 Prompt；运行前请先检查来源。

npx skills add https://github.com/google/adk-python --skill adk-style

命令会保持在同一行。复制前请横向滚动并检查完整内容。

想先保存到本地？可下载 SkillsMP 当前能够提供的文件。

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决定是否安装前，请先阅读 SKILL.md，以及 SkillsMP 当前展示的配套文件。

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11 个文件

SKILL.md

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name: adk-style
description: Python style and codebase conventions for ADK (Agent Development Kit): private-by-default file visibility, imports, type hints, Pydantic v2 models, formatting, docstrings, logging, async I/O, file and test layout, and unit test structure. Use when writing or editing ADK source or tests, deciding whether a new file or symbol should be public or private, naming or placing a test file, fixing a formatter, linter, or type-check failure (pyink, isort, ruff, mypy, addlicense, compliance-checks), or asking whether code matches house style. Don't use for reviewing a whole changeset (use adk-review), writing a developer guide or design doc for a code unit (use adk-unit-guide or adk-unit-design), building or configuring agents (use adk-agent-builder), or installing the toolchain (use adk-setup).

# ADK Style Guide Conventions for `src/google/adk/` and `tests/unittests/`. Most are enforced by a pre-commit hook or a CI job, so a violation blocks the PR rather than surfacing in review. Read the one reference for the topic you are touching. ## Pick a reference | Task | Reference | | --- | --- | | Adding a `.py` file; deciding public vs private; `__init__.py` and `__all__` | [visibility.md](references/visibility.md) | | Writing `import` lines; relative vs absolute; circular imports; `TYPE_CHECKING`; lazy imports | [imports.md](references/imports.md) | | Annotating args and returns; `AgentMode` vs raw mode strings; `_NodePathBuilder`, `_BranchPath`, and `build_node`; `Optional` vs `\| None`; keyword-only args; `isinstance`; asserts; mypy; `# type: ignore` and `cast` | [typing.md](references/typing.md) | | Defining a Pydantic model, validator, private attribute, or on-wire payload | [pydantic.md](references/pydantic.md) | | Indentation, line length, quotes; running the formatter; what each hook checks | [formatting.md](references/formatting.md) | | Writing a docstring or an explanatory comment | [documentation.md](references/documentation.md) | | Emitting a log record; naming the module logger; picking a level | [logging.md](references/logging.md) | | Anything that performs I/O — network, disk, database | [async.md](references/async.md) | | Where a new file goes; license header; where its test goes and what to call it | [file-organization.md](references/file-organization.md) | | Writing or restructuring a unit test; the `testing_utils` fakes | [testing.md](references/testing.md) | ## A check failed — where to look | Failing check | Reference | | --- | --- | | `check-new-py-prefix` | [visibility.md](references/visibility.md) | | `compliance-checks` | [logging.md](references/logging.md) (logger name), [typing.md](references/typing.md) (`from __future__ import annotations`), [imports.md](references/imports.md) (`cli/` import direction) | | `pyink`, `isort`, `ruff`, `addlicense`, `codespell` | [formatting.md](references/formatting.md) | | Mypy Check CI job | [typing.md](references/typing.md) | | `tests/unittests/test_import_loading.py` | [imports.md](references/imports.md) |

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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).

2026-10-09

adk-review

Reviews the uncommitted changes in an adk-python working tree and reports correctness, design, public-API stability, test, sample and documentation gaps as a prioritized findings report, fixing them only when asked. Use when the user asks to review local changes, wants a self-review before opening a pull request, asks whether a change breaks the public API or needs tests, samples or docs, or asks what is wrong with the current diff. Required for changes to public APIs, core architecture (Runner, Workflow, BaseNode), new features and major refactors. Don't use for a single style nit (use adk-style), for diagnosing a failing test or a misbehaving agent at runtime (use adk-debug), or for wording a commit message or PR description (use adk-git).

2026-10-09

bigquery-ai-ml

Leverages BigQuery's built-in machine learning and GenAI capabilities for advanced data analytics. Use when you need to write SQL queries that perform time-series forecasting, predict values, detect outliers or anomalies, find key drivers, perform semantic search or vector search, classify text, calculate similarity, summarize content, translate language, evaluate models, filter by semantic conditions, measure the causal effect of an intervention, compute correlations between columns, detect change points or structural breaks, extract trend or seasonality components, or leverage generative AI capabilities in BigQuery. Do not use for general BigQuery dataset, table, or job management requests.

2026-10-08

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