execute

Enforce a gated QA pipeline with retries and pre-commit compliance checks.

437|45|Updated Jan 27, 2026
One-click install
npx skills add https://github.com/ZaxbyHub/opencode-swarm --skill execute-zaxbyhub
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: execute
Source: https://github.com/ZaxbyHub/opencode-swarm/tree/main/.opencode/skills/execute
Command: npx skills add https://github.com/ZaxbyHub/opencode-swarm --skill execute-zaxbyhub

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill solves the critical risk of unvalidated AI-generated code reaching production by enforcing a strict, multi-step gated execution pipeline with mandatory retries, verification checks, and pre-commit compliance rules.

Core Features & Use Cases

  • Gated QA Pipeline: Orchestrates syntax checks, placeholder scans, dependency audits, linting, build checks, security scans, and code review gates in sequence, with automatic coder retries for any failed gate.
  • Verification & Compliance: Includes post-coder write verification, regression sweeps, test drift checks, and a mandatory pre-commit checklist to ensure no code ships without passing all required quality and security standards.
  • Use Case: Software engineering teams using AI coding assistants can use this Skill to eliminate broken or vulnerable code from reaching production, reducing post-deployment bugs and security incidents.

Quick Start

Use the execute skill to run the full gated QA pipeline for your current AI coding task, enforcing all required checks and retries before allowing a commit.

Frequently Asked Questions about execute

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

FAQPage Schema
How do I enforce pre-commit checks for AI-generated code before it reaches production?

AI coder retry logic automatically triggers when a QA gate fails, forcing the AI coding assistant to correct and resubmit the code until it passes all required quality, security, and compliance validations.

What security scanning and QA gating steps are required for safe AI code execution?

A gated QA pipeline orchestrates verification by running post-coder write verification, regression sweeps, and test drift checks, generating completion evidence to validate code quality before final commit approval.

Does this gated execution pipeline support automated regression sweep execution?

The pipeline enforces regression sweeps alongside security scanning and code review gates, orchestrating verification steps to eliminate broken code and generate mandatory completion evidence for task closure.

How do I stop unvalidated AI-generated code from reaching production environments?

This gated execution approach eliminates the risk of broken code by enforcing pre-commit compliance rules and automatic coder retries for any failed QA gate, ensuring all code is validated before shipping.

What is the best way to automate code review and dependency audits for AI coding tasks?

By orchestrating mandatory checks like dependency audits, linting, and security scans in a strict sequence, the pipeline ensures all AI coding tasks meet pre-commit compliance standards before final commit.

Are there limitations to using automated QA gating for AI code execution?

This strict gating means no code ships without passing mandatory pre-commit compliance validation, which may slow down rapid prototyping but ensures no unvalidated or broken code reaches production.