brainstorming
brainstorming
You MUST use this before any creative work - creating features, building components, adding functionality, modifying behavior, or planning anything new, in software or out of it (a talk, a business, a renovation).
langchainWork on the LangChain Python monorepo: package routing, core primitives, v1 agents and middleware, classic APIs, partner integrations, standard tests, model profiles, and safe validation workflows.
Independent GitHub snapshot · Automated classification · Original documentation governs
Use this skill when a task targets the LangChain Python repository, its package-local development workflow, or one of its maintained Python packages.
uv, pytest, lint, type, import, and version checks.langchain-core primitives such as runnables, messages, prompts, tools, documents, embeddings, vector stores, model interfaces, callbacks, parsers, serialization, and deprecation utilities: use core-primitives.langchain v1 APIs such as init_chat_model, create_agent, structured output, tools, middleware, embeddings, provider routing, and agent runtime customization: use agents-and-middleware.langchain-classic chains, retrievers, document loaders/transformers, memory, indexes, classic agents, evaluation, and legacy maintenance or migration: use classic-chains.libs/partners, provider SDK dependencies, credentials, unit/integration test split, cassettes, vector-store services, and provider model profile data: use integrations.langchain-tests, native verification selection, pytest marker/snapshot safety, model-profile CLI internals, and safe test/profile command planning: use testing-and-profiles.libs/core publishes langchain-core, the stable abstraction layer used by other packages.libs/langchain_v1 publishes langchain, the actively maintained high-level package.libs/langchain publishes langchain-classic, a legacy compatibility package; avoid new feature work there unless explicitly requested.libs/text-splitters publishes langchain-text-splitters, focused on chunking documents and text.libs/partners/<provider> publish maintained provider integrations such as OpenAI, Anthropic, Ollama, Qdrant, Chroma, DeepSeek, Fireworks, Groq, Hugging Face, MistralAI, Nomic, Perplexity, OpenRouter, xAI, and Exa.libs/standard-tests publishes langchain-tests, shared conformance tests for integrations.libs/model-profiles contains the model profile refresh CLI and provider profile tooling.Run commands from the owning package directory unless a package reference says otherwise:
cd libs/<package>
uv sync --group test
uv run --group test pytest tests/unit_tests/path/to/test_file.py
make lint_package
make type
Use narrower commands first. Add --group lint, --group typing, --group test_integration, or --all-groups only when the package metadata and task require those dependencies. Do not use pip, poetry, conda, or ad-hoc virtual environments for normal LangChain development.