A coding agent needs documentation that matches the installed package and the API it is using. Faster retrieval of an obsolete example does not solve the task. Record the package version, intended operation and official source before admitting a snippet into the agent context.
Make version identity part of the research request
| Field | Purpose |
|---|---|
| Package and installed version | Identify the actual runtime |
| Operation and API family | Avoid mixing legacy and current contracts |
| Official documentation URL | Make the authority traceable |
| Access date and relevant passage | Retain current evidence |
| Local test outcome | Separate an imported symbol from a working example |
Select sources before parallel reading
Search for the operation and version, then prefer the package’s official documentation or source repository. Deduplicate links that represent the same documentation page. Keep incompatible legacy examples in a rejected-source record rather than mixing them into the final prompt.
For this revision, installed LangChain, LangGraph, LlamaIndex and google-genai examples were checked with local mocks or fixtures. Those checks exposed integration boundaries; they did not measure a coding agent’s success rate or perform paid model generation.
Test the smallest claim the snippet makes
Parallel scheduling belongs after source selection and inside a finite work budget. This page concerns version-matched coding evidence, not a generic promise that concurrent search improves code quality.
- Check the current import path and function signature.
- Run a small controlled input with the actual installed package.
- Keep a failure case or a stop condition where the operation can repeat.
- Record what remained untested, especially external services and model behavior.
Reference documentation: docs.langchain.com — /oss/python/langchain/agents; docs.langchain.com — /oss/python/langgraph/graph-api; ai.google.dev — /gemini-api/docs/google-search.
