# Coordinate Complete Feature Development

Complex feature work can stall when research, architecture, implementation, testing, and documentation are handled separately. This skill coordinates a staged workflow that guides Claude, Codex, and Gemini through delivery checks.

## Install

```bash
npx skillstore add dnyoussef/feature-dev-complete
```

## Metadata

- Status: approved
- Slug: dnyoussef-feature-dev-complete
- Version: 1.0.0
- Author version: 1.0.0
- Skillstore revision: r1
- Version status: valid
- Tree hash: f5b67af8ffcef9d69b0d9fbf9ca9b873be52f1aa2bbb9bdfd4bdac5001ee7e73
- Author: DNYoussef
- GitHub username: DNYoussef
- License: MIT
- Repository: https://github.com/DNYoussef/ai-chrome-extension/tree/main/.claude/skills/feature-dev-complete
- Ref: 72d5025b022c77f7a51bdf5c1637c689c80e89d1
- Supported tools: Claude, Codex, Claude Code
- Audit status: complete
- Agent install advisory: confirmation\_required
- Manual install advisory: allowed
- Artifact signature: available
- Audit attestation: unavailable
- Human verification: not\_verified
- Risk factors: external\_commands, filesystem
- Quality score: 38
- Quality tier: warning
- Public page: https://skillstore.pages.dev/skills/dnyoussef-feature-dev-complete
- Manifest: https://skillstore.pages.dev/api/skills/dnyoussef-feature-dev-complete/manifest

## Capabilities

- Defines a 12-stage workflow from research through deployment readiness.
- Assigns roles to Gemini, Claude, Codex, and related workflow commands.
- Specifies artifacts for research, architecture, diagrams, implementation, tests, documentation, and quality reports.
- Includes quality gates for test status, quality score, and critical security issues.
- Documents integration points with related cascades, commands, and skills.

## Use Cases

- Plan a New Product Feature: Turn a feature request into research notes, architecture direction, implementation tasks, and quality gates.
- Coordinate Implementation Work: Use a staged process to prototype, test, polish, and document a feature before review.
- Prepare Release Evidence: Collect test, style, security, documentation, and readiness outputs for a pull request review.

## Prompt Templates

### Start a Feature Plan

```
Use this skill to plan the feature: [describe the feature]. Keep the target directory unchanged until I approve implementation.
```

### Design Before Building

```
Research current best practices for [feature], analyze existing patterns in [directory], and draft an architecture plan with risks and test strategy.
```

### Run Guarded Implementation

```
Implement [feature] in [directory] using staged checkpoints. Ask before file copy, git operations, external service calls, or pull request creation.
```

### Prepare Review Package

```
Create a release readiness package for [feature] with test results, quality findings, security review notes, documentation changes, and unresolved decisions.
```

## Limitations

- Requires external tools such as Gemini, Codex, npx, jq, git, and gh.
- The main workflow is documented as shell script text, not packaged executable code.
- Full automation can modify repository files and create commits or pull requests.
- The codebase size check focuses on JavaScript and TypeScript files.

## Best Practices

- Run the workflow on a branch or disposable workspace before touching production code.
- Review research, architecture, and generated changes before allowing commit or pull request steps.
- Confirm external model usage is acceptable before sending repository context to AI services.

## Anti Patterns

- Do not enable full automation in a repository that contains uncommitted or sensitive work.
- Do not skip the security and quality gates just to create a faster pull request.
- Do not use this workflow when the feature scope or target directory is unclear.

## Security Audit

- Audited at: 2026-07-06T12:12:17.058\+00:00
- Summary: Most static hits are false positives from Markdown fences, inline command names, and fixed local report parsing in an example shell workflow. The skill still carries meaningful risk because it instructs users or agents to run external AI tools, automate source changes, and create commits or pull requests.

## Stats

- Views: 257
- Downloads: 8
- Favorites: 0
- Popularity score: 0