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feat(review): specialized multi-agent review with parallel agentic workflow

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#63 2 comments 0 reactions 0 assignees View on GitHub

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Assessment

Difficulty
5/5
Estimated time
Over a week
Newbie friendliness
35/100
Issue type
Feature
Clarity
Mostly clear
Activity status
Quiet
Tech stack
java
Domain
ai, backend

Research direction

Start by reading the existing PrReviewer, FindingDeduplicator, and FindingVerifier implementations and the project’s Quarkus native build configuration. Then check whether the configured model provider supports tool calling and review the quarkus-langchain4j-agentic module’s native compatibility. Done means parallel specialized reviews are merged and deduplicated, verified by the existing verifier, and validated in the native build.

Written by the indexing model from the issue text.

Description

enhancement help wanted java
Problem Statement

The bot runs a single review pass (PrReviewer) plus a second-pass verifier. One prompt must cover correctness, security, regressions, comment consistency, and code quality at once, which dilutes focus and makes any single dimension hard to tune or extend. Specialized agents — each focused on one concern, running in parallel and merged — would improve depth and let each concern evolve independently.

Proposed Solution

Adopt the quarkus-langchain4j-agentic module and run specialized review agents (e.g. correctness, security, regression, code-quality/consistency, test-coverage) as a parallel agentic workflow, then merge and dedupe their findings (reuse FindingDeduplicator) and pass the result through the existing verifier (FindingVerifier).

  • Agents can be given @Tool methods (e.g. fetch a related file, look up a symbol) to deepen context — pairs with #55 (codebase-aware context).
  • Account for the added token cost via the per-PR spend cap (#42); allow cheaper concerns to use cheaper models via risk-based routing (#43).
  • Validate the agentic module in the GraalVM native build, and confirm the configured provider supports tool/function calling (tool use is model-dependent).
Alternatives Considered
  • Single combined prompt + verifier (current) — cheapest, but one prompt juggling all concerns limits depth and tunability.
  • Sequential agents — simpler orchestration, but higher latency than running concerns in parallel.
Priority

Important

Code of Conduct
  • I have searched for existing issues and this is not a duplicate.
Dominant language
Java
Stars
35
Forks
7
Avg merge
9h 32m
Merged PRs (30d)
144

Getting set up

First steps

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  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

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