A smarter way to run code migrations with less LLM context

Deep Search uses sandboxed scripts around Sourcegraph search APIs to perform large-scale codebase audits and migrations without sending thousands of files and intermediate search results to an LLM. Rather than relying on standard agent workflows that process all raw data in a model’s context window, it runs searches, filters and cross-references findings, calculates totals, and generates structured outputs such as CSV, JSON, and SVG reports, passing only aggregated results to the model. This approach is intended to reduce token costs, limit irrelevant context, and produce more actionable results for tasks such as identifying imports of deprecated packages, locating TODO-heavy files, tracking shared-service usage, detecting outdated dependencies, and comparing implementation patterns.

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