sqd

Community

Parallel adversarial reviews across LLMs.

AuthorEndUser123
Version1.0.0
Installs0

System Documentation

What problem does it solve?

SDLC teams often need fast, diverse quality reviews across multiple LLM providers to surface blind spots and contested findings. SQD addresses this by running parallel adversarial reviews and synthesizing results.

Core Features & Use Cases

  • Parallel orchestration of reviews across selected LLM providers (DeepSeek, Gemini, Claude, GPT) to surface divergent findings.
  • Consolidated synthesis of findings to a consensus or highlight the need for deeper audit.
  • Output artifacts including per-model findings and a synthesis report to support shipping decisions.

Quick Start

Dispatch a parallel adversarial review to the selected models for a given target artifact.

Dependency Matrix

Required Modules

None required

Components

Standard package

💻 Claude Code Installation

Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.

Please help me install this Skill:
Name: sqd
Download link: https://github.com/EndUser123/sdlc/archive/main.zip#sqd

Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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