docs-retrieval

Retrieve local documentation context by enforcing a local-first lookup from the ai-docs hierarchy, formatting results into structured context blocks for sub-agents. This approach prioritizes targeted page summaries to inform AI-driven tasks efficiently.

Multi-library context consolidation gathers library docs and pages from local storage into a single context block. This minimizes token use while preserving key insights needed for cross-cutting development tasks.

Yes, token-budget awareness is maintained by prioritizing targeted page summaries during local doc retrieval. This minimizes token use while preserving key insights required by sub-agents.

Local-first documentation retrieval works for implementing features, debugging errors, and seeking library information. It enforces local-first lookup from the ai-docs hierarchy to inform tasks directly.

Prepare structured context blocks by retrieving targeted local docs and returning a concise summary. The system formats results into structured context blocks ready for sub-agent use with token-budget awareness.

Local-first retrieval patterns are limited to the documentation available within the local ai-docs hierarchy. If specific library pages or patterns are not stored locally, the retrieval process cannot access external documentation.