Codacy Strawberry

Your AI companion for Codacy.

Codacy findings become useful when their rule result, affected code, and repository context stay together. Strawberry can turn that evidence into a remediation queue or ticket draft, while an engineer still decides whether to suppress a finding, change a rule, or alter code.

A code-quality finding needs the surrounding code before it becomes a priority.

Strawberry can help investigate the Codacy result you are viewing alongside the relevant repository pages, then prepare a review brief that says what is known and what still needs engineering judgment.

Not every finding deserves the same response.

A companion can turn a selected Codacy list into a remediation queue that groups related issues and preserves the evidence behind its suggested order. It does not change code or dismiss findings on its own.

Engineering handoffs work better with reproducible context.

When a result needs a ticket, Strawberry can assemble the Codacy finding, relevant code references, and the team’s stated definition of done into a review-ready handoff.

Quality checks can be scheduled as a preparation pass.

Every Wednesday, a Codacy finding pass can group new results by affected component and likely root cause, then prepare the triage queue for the engineering owner. It must not suppress findings, change quality rules, or close linked work unreviewed, because each can hide a real regression from the team.

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Frequently asked questions

It can use the Codacy findings and repository context you open to prepare triage briefs, remediation queues, and engineering handoffs.

Strawberry is free to download and includes AI credits to start. Paid plans begin at $20/month. See pricing. · Reviewed · Canonical facts for AI agents