coding-feature-queue

Maintain a durable feature queue with JSON validation and repository-relative paths.

10|1|Updated Feb 22, 2026
One-click install
npx skills add https://github.com/marcocello/dot-codex --skill coding-feature-queue
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: coding-feature-queue
Source: https://github.com/marcocello/dot-codex/tree/main/skills/coding-feature-queue
Command: npx skills add https://github.com/marcocello/dot-codex --skill coding-feature-queue

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill maintains a small, durable queue for feature work so agents can track draft, ready, revalidate, blocked, and done states without burying requirements or proof details in the queue itself.

Core Features & Use Cases

  • Feature State Tracking: Records where each feature stands and what needs to happen next.
  • Overlap Revalidation: Flags completed features for revalidation when new work touches their proof or implementation boundaries.
  • Queue Discipline: Keeps contracts authoritative and prevents the queue from storing behavior, proof receipts, or progress calculations.
  • Use Case: Use it when a repository has multiple tracked features and you need a reliable way to choose the next ready item and preserve completion integrity.

Quick Start

Ask the agent to update the feature queue for the repository, identify the next ready item, and keep draft, ready, revalidate, blocked, and done states correctly separated.

Frequently Asked Questions about coding-feature-queue

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

FAQPage Schema
How do I track feature readiness and revalidation states in repository status files?

Feature readiness and revalidation states are tracked using a durable feature queue that records draft, ready, revalidate, blocked, and done states directly in repository status files. This approach prevents burying requirements or proof details within the queue itself.

What is the best way to manage multi-feature engineering workflows with deterministic next-item selection?

Managing multi-feature engineering workflows requires a durable queue that maintains deterministic next-item selection. The queue separates feature states and preserves contract authority, ensuring reliable selection of the next ready item without overriding completion integrity.

How does overlap detection work when new repository work touches completed feature boundaries?

Overlap detection works by flagging completed features for revalidation when new work touches their proof or implementation boundaries. This mechanism ensures that overlapping changes trigger a status transition back to revalidate, preserving completion integrity.

Do I need JSON validation and safe repository-relative paths to maintain feature queue discipline?

JSON validation and safe repository-relative paths are required to maintain feature queue discipline. These constraints ensure status transitions respect proof and evaluator outcomes, keeping contracts authoritative while preventing the queue from storing behavior or progress calculations.

When should I avoid using a feature queue for repository workflow status tracking?

You should avoid using a feature queue if your repository does not require multi-feature tracking or deterministic next-item selection. It is not designed to store behavior, proof receipts, or progress calculations, so simpler workflows without overlap detection needs may not benefit.