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andyzengmath
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ql-review

Orchestrate two-stage code review enforcing spec compliance before quality checks.

24|Updated Feb 16, 2026
Search Tags:#git#code review#lsp#spec compliance#quality review#integration review#quantum.json
One-click install
npx skills add https://github.com/andyzengmath/quantum-loop --skill ql-review
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: ql-review
Source: https://github.com/andyzengmath/quantum-loop/tree/main/skills/ql-review
Command: npx skills add https://github.com/andyzengmath/quantum-loop --skill ql-review

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Prevents wasted review effort and unsafe merges by enforcing spec compliance before any code quality evaluation, ensuring that only implementation-accurate changes consume reviewer time and CI gates.

Core Features & Use Cases

  • Two-stage review pipeline: Stage 1 validates code against PRD acceptance criteria and Stage 2 assesses code quality only if Stage 1 passes.
  • Standalone and automated modes: Can be invoked manually against a branch or run automatically as part of the quantum-loop execution using quantum.json context.
  • Integration checks: Performs cross-story call-chain tracing, type consistency checks, dead-code detection, and import resolution using LSP when available, with grep/fallbacks as needed.
  • Clear gating and remediation: Emits structured reports, records results to quantum.json when present, enforces fix-and-retry semantics, and provides exact wiring fixes for integration failures.

Quick Start

Run ql-review against the current story or branch to perform a spec compliance review followed by a code quality review.

Frequently Asked Questions about ql-review

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How does a spec-first code review pipeline work?▼

A spec-first code review pipeline validates code changes against PRD acceptance criteria before running quality checks, ensuring only spec-compliant changes proceed to quality evaluation and merge gates.

What is the best way to automate code review for a git branch diff?▼

Automate code review for a git branch diff by running a two-stage pipeline against BASE_SHA and HEAD_SHA ranges, requiring quantum.json context or a PRD path with acceptance criteria to gate merges.

Can I perform cross-story integration checks for call chains without LSP tools?▼

Yes, you can perform cross-story integration checks using grep fallbacks for call tracing, type consistency checks, dead-code detection, and import resolution when LSP tools are not available in your environment.

Why does code quality review fail when spec compliance is not met?▼

Code quality review fails or is skipped when spec compliance is not met because the two-stage pipeline enforces spec validation first, preventing wasted review effort on implementation-inaccurate changes.

Do I need quantum.json to run a standalone branch code review?▼

No, you do not need quantum.json for a standalone branch review if you provide a PRD path and acceptance criteria along with BASE_SHA and HEAD_SHA git ranges for the diff evaluation.

How do I fix integration failures found during a code review?▼

To fix integration failures found during a code review, apply the exact wiring fixes provided in the structured report, then retry the review pipeline which enforces fix-and-retry semantics for failed checks.

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