菜单
Code quality standards, formatting, commit conventions, and PR workflow for Agent Kernel development. Use this skill when making contributions, formatting code, writing commit messages, or preparing pull requests.
用 Codex 或 Claude 帮你安装 复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。
基于 SOC 职业分类
Agent Kernel architectural principles, core abstractions, and design patterns. Use this skill when you need to understand the codebase structure, how components interact, or before making changes to core functionality. Covers Session, Agent, Runner, Module, Runtime, AgentService, AKConfig, tools, hooks, multimodal, conversation threads, the adapter pattern, and the AWS ECS containerized deployment classes (ECSIOHandler, ECSOutputConsumer, ECSAgentRunner, ECSSQSConsumer, QueueConsumer, ThreadRunner).
Step-by-step guide for adding a new multimodal attachment storage backend to Agent Kernel. Use this skill when you need to integrate a new storage service (beyond in-memory, Redis, and DynamoDB) for persisting image and file attachments. Covers implementing the AttachmentStore interface, factory registration, configuration, and testing.
Testing conventions, patterns, and automation for Agent Kernel development. Use this skill when writing tests for new features, debugging test failures, or understanding the test infrastructure. Covers pytest patterns, async testing, mocking, the built-in Test framework, and CI/CD test workflows.
Review a GitHub pull request against Agent Kernel's architecture, design principles, code quality standards, and testing conventions, then post the findings back to the PR as review comments. When the PR contains spec documents (design.md, spec.md, or plan.md under docs/specs/), they are reviewed first — each at its own stage's altitude — and any implementation is checked against them. Use this skill when given a PR number or URL to review, e.g. "review PR 342" or "run a review on https://github.com/yaalalabs/agent-kernel/pull/342".
Write the spec documents for a planned Agent Kernel change under docs/specs/<ticket>/ in three ordered stages: a concise point-form design spec (design.md) that a maintainer reviews first, then a detailed implementation spec (spec.md) once the design is approved, then a concise implementation plan (plan.md). Use this skill when asked to write or update a design, spec, or plan for a feature, refactor, or fix before it is implemented, e.g. "write a design spec for AK-52" or "spec out the shared driver extraction".
Add capabilities to an existing Agent Kernel project. This skill guides you through adding guardrails, tracing/observability, session persistence, knowledge bases, MCP server, A2A server, pre/post hooks, multimodal support, and conversation thread support. Session persistence supports Redis, DynamoDB (AWS), Cosmos DB (Azure), and Firestore (GCP). Conversation threads support in-memory, Redis, DynamoDB (AWS), Firestore (GCP), and Cosmos DB (Azure) backends. Generates configuration and code changes needed.
| name | ak-dev-code-quality |
| description | Code quality standards, formatting, commit conventions, and PR workflow for Agent Kernel development. Use this skill when making contributions, formatting code, writing commit messages, or preparing pull requests. |
| license | Apache-2.0 |
| metadata | {"author":"yaalalabs","category":"developer"} |
Agent Kernel uses black for formatting and isort for import sorting.
# Format ak-py source and tests
make lint
# Format examples too
make lint-all
make lint-check # ak-py only
make lint-check-all # ak-py + examples
In ak-py/pyproject.toml:
[tool.black]
line-length = 150
target-version = ["py312"]
[tool.isort]
profile = "black"
line_length = 150
In example projects, line length is 120:
[tool.black]
line-length = 120
target-version = ["py312"]
cd ak-py
uv run mypy src/
Configuration:
[tool.mypy]
python_version = "3.12"
warn_return_any = true
warn_unused_configs = true
disallow_untyped_defs = true
disallow_incomplete_defs = true
Use Conventional Commits format:
<type>: <short description>
| Type | When to Use |
|---|---|
feat: | New feature or capability |
fix: | Bug fix |
docs: | Documentation changes only |
chore: | Maintenance, dependencies, config |
refactor: | Code restructuring without behavior change |
test: | Adding or modifying tests |
feat: add telegram messaging integration
fix: handle empty session in Redis store
docs: update deployment guide for Azure containerized
chore: bump openai-agents dependency to 0.6.5
refactor: extract common guardrail logic to base class
test: add unit tests for CosmosDB session store
feat: add telegram integration (#123)Branch from and target develop, not main — CI (.github/workflows/code-quality.yml) runs on pull requests against develop, and origin/HEAD points there.
cd ak-py && uv run pytestmake lint-check-allak-py/src/agentkernel/core/docs/, README filesHandled by publish.yaml workflow. This updates:
This updates:
ak-py/pyproject.toml version fieldThe version appears in:
ak-py/pyproject.toml → version = "x.y.z"version fields in examplesagentkernel dependency version constraints in example pyproject.toml filesuv package managergit clone https://github.com/yaalalabs/agent-kernel.git
cd agent-kernel
make dev-setup # Installs pyenv, Python 3.12, uv, then syncs ak-py venv
# or directly: ./scripts/dev-setup.sh
Alternatively, set things up manually:
cd agent-kernel/ak-py
./build.sh # Creates venv, installs deps
cd examples/cli/openai
./build.sh
uv run demo.py
cd examples/cli/openai
./build.sh
uv run pytest -s
ak-py/src/agentkernel/ — all package source codeak-py/tests/ — unit testsexamples/<mode>/<framework>/ — self-contained demo projectsdocs/docs/ — Docusaurus documentationscripts/ — CI/CD and maintenance scriptsak-deployment/ — Terraform modules|, match statements)logging.getLogger("ak.<module>") for logger namesBaseModel (Pydantic) for data modelsABC and @abstractmethod for interfaces"ak"): Parent logger for all Agent Kernel components
"ak.api", "ak.runtime", etc. inherit from thislogging.getLogger("ak.<module>") for Agent Kernel componentsThe following log levels are supported (in order of verbosity):