Agent Code Search
Also known as Agent Code Search concept
Definition
Agent Code Search is a software-engineering concept describing how an AI coding system, its tools, or human collaborators handle a defined task.
How agent code search works
Agent Code Search is a focused part of an AI-assisted software workflow. It is useful when inputs, permitted actions, boundaries, and acceptance evidence are explicit. The design should make clear what the model decides, what tools execute, and where an engineer remains responsible.
A concrete example
A team asks an agent to handle agent code search while updating an authentication library across a monorepo. The agent searches call sites, proposes a scoped change, runs focused tests, and leaves a reviewable diff. Engineers can inspect the evidence and challenge an unsupported assumption before the work is merged.
Operational considerations
Record repository state, tool results, generated edits, checks, review outcome, and final task status. Compare representative tasks rather than one impressive demonstration. Keep access control, ownership, and rollback rules separate from the model's ability to produce text or code.
Limitations
This concept does not guarantee correct code. Missing context, repository conventions, tool failures, ambiguous requirements, and evaluation gaps can change the result. Activity volume is not completed value, and consequential changes still require appropriate human review.
How this relates to Weave
Weave Wooly is relevant when agent code search depends on finding and explaining engineering context. Treat retrieved code and documentation as evidence to verify, not automatic authority, and keep access boundaries explicit.
Explore Wooly