Review

/review — Multi-Agent Code Review

You are performing a thorough code review of recent changes using multiple specialized review agents.

This skill is the pre-push ADLC review gate. It runs 5 specialized review agents in parallel, covering the same dimensions the CI llm-review workflow would cover if it ran (correctness, conventions, test coverage, security) plus an architecture dimension the CI workflow doesn't have. Running this before pushing means the ADLC gate catches issues regardless of whether the CI layer is available — CI-layer LLM reviews can be blocked (billing, infra, outages) and must not become the sole safety net.

Ethos

!test -s .adlc/ETHOS.md && cat .adlc/ETHOS.md || echo No ethos found — run /init to vendor .adlc/ETHOS.md

Context

• Current branch: !git branch --show-current || echo Not a git repo
• Committed changes vs main: !git diff-tree --stat -r main HEAD || echo No diff available
• Uncommitted changes: !git status --short

Context files loaded on demand: .adlc/context/conventions.md and recent lessons are loaded by Step 1 below — skip the Reads if they are already in the current conversation (e.g., when invoked from /proceed, which preloads conventions.md at Phase 0).

Input

Scope: $ARGUMENTS

Prerequisites

Before proceeding, verify that .adlc/context/conventions.md exists. If it doesn't, stop and tell the user: "The .adlc/ structure hasn't been initialized. Run /init first to set up conventions."

Instructions

Step 1: Determine Review Scope and Load Context

1. If given specific file paths, review those files
2. If given a branch name, review all changes on that branch vs main
3. If given a REQ/TASK ID, find the associated branch and review its changes
4. If no argument, review all uncommitted changes + commits on the current branch vs main
5. Get the full diff: git diff main...HEAD (or git diff for uncommitted changes)
6. Conventions: if .adlc/context/conventions.md is NOT already in your conversation context, Read it now. Otherwise skip — it's already loaded.
7. Relevant lessons (mirrors the spirit of llm-review.yml, but relevance-ranked instead of time-ranked): a. Derive the set of touched components from the diff. Components are inferred from file paths — e.g. api/auth/* → API/auth, app/Sources/Views/*.swift → iOS/SwiftUI, infrastructure/terraform/* → infra/terraform. Produce a short list of plausible component values and a broader list of domain values (e.g. API, iOS, infra). b. Glob .adlc/knowledge/lessons/*.md and read each file's frontmatter (domain, component, tags). Keep lessons where component matches any touched component exactly, OR where domain matches any touched domain AND component is a prefix of a touched component, OR where any tag matches a touched component/domain. This is the relevance set. c. If the relevance set has fewer than 5 entries, top it up with the most recently modified lessons from .adlc/knowledge/lessons/ (the previous time-based heuristic) until the set has up to 10 entries. This keeps small or cross-cutting diffs from losing context entirely. d. Cap the final list at 15 lessons. Read their bodies in full. e. Pass the content of every selected lesson as context to every review agent in Step 3. When a finding later matches one of these lessons, cite its id explicitly (Step 4 uses this to elevate severity). Fallback: if any lesson has no component / domain / tags frontmatter (legacy file), fall back to reading its title + first paragraph and include it only if the title contains any touched domain or component substring. Do not skip it silently — it may be load-bearing.

Step 2: Read All Changed Files

Read the complete current version of every changed file (not just the diff) to understand full context.