# Start Quetrex Development Sessions

Quetrex sessions need current project context before useful development work can begin. This skill gives Claude, Codex, and Claude Code a concise workflow map for issues, automation, quality gates, and project status.

## Install

```bash
npx skillstore add barnhardt-enterprises-inc/quetrex-development-workflow
```

## Metadata

- - Slug: barnhardt-enterprises-inc-quetrex-development-workflow
- - Version: 1.0.0
- - Author: Barnhardt-Enterprises-Inc
- - GitHub username: Barnhardt-Enterprises-Inc
- - License: MIT
- - Repository: https://github.com/Barnhardt-Enterprises-Inc/quetrex-plugin/tree/main/templates/skills/quetrex-development-workflow
- - Ref: main
- - Supported tools: Claude, Codex, Claude Code
- - Risk level: medium
- - Risk factors: external\_commands
- - Quality score: 73
- - Public page: https://skillstore.pages.dev/skills/barnhardt-enterprises-inc-quetrex-development-workflow
- - Manifest: https://skillstore.pages.dev/api/skills/barnhardt-enterprises-inc-quetrex-development-workflow/manifest

## Capabilities

- Explains the Quetrex product purpose, core capabilities, and technology stack.
- Shows how AI-agent issues trigger GitHub Actions and Claude Code automation.
- Provides examples for creating well-scoped issues with acceptance criteria.
- Summarizes quality gates, testing expectations, and development patterns.
- Points users to project status, memory files, architecture docs, and checklists.

## Use Cases

- Start a Quetrex Coding Session: Load project context, identify pending work, and choose whether to create an agent issue or work directly.
- Prepare AI-Agent Issues: Write focused feature requests with acceptance criteria, file references, test expectations, and priority levels.
- Review Agent Automation Output: Inspect AI-generated pull requests, check workflow runs, review logs, and apply the documented quality gates.

## Prompt Templates

### Begin a Session

```
Use the Quetrex development workflow to summarize the project, list the current workflow steps, and identify the first safe action.
```

### Create an Agent Issue

```
Help me turn this feature idea into a Quetrex AI-agent issue with clear acceptance criteria, relevant files, tests, and priority.
```

### Review a Pull Request

```
Use the Quetrex workflow to review an AI-agent pull request. Focus on quality gates, tests, architecture fit, and merge readiness.
```

### Debug a Failed Workflow

```
Guide me through debugging a failed Quetrex AI-agent workflow run. Identify the likely failure source and the next verification steps.
```

## Limitations

- It is tailored to the Quetrex repository structure and naming conventions.
- It depends on GitHub CLI access for live issue, PR, and workflow commands.
- It does not verify whether referenced project files are current.
- It guides workflow decisions but does not enforce repository permissions.

## Best Practices

- Confirm the target repository and branch before running GitHub CLI commands.
- Use focused issues with acceptance criteria, file references, and test expectations.
- Review AI-agent pull requests with the same standards as human-authored changes.

## Anti Patterns

- Do not combine unrelated features into one AI-agent issue.
- Do not merge generated pull requests before reviewing tests and changed files.
- Do not rely on stale status documents without checking live issues and pull requests.

## Security Audit

- - Safe to publish: true
- - Audited at: 2026-06-28T12:52:56.923\+00:00
- - Summary: Static analysis found many command-like strings, but review shows they are GitHub CLI and git workflow examples for a Quetrex development process. The Windows SAM and weak cryptography alerts are false positives from ordinary project text and filenames. The skill is publishable with a warning because it instructs users to run external commands that can modify GitHub state.

## Stats

- - Views: 235
- - Downloads: 5
- - Favorites: 0
- - Popularity score: 0