feature-tracking

Feature Tracking

Overview

Feature Tracking maintains lightweight, repository-native memory for long-lived feature work. It gives AI coding agents a stable place to find the current status, authoritative documents, verified behavior, durable decisions, risks, and recent changes without treating chat history or stale plans as truth.

The workflow uses a global index plus one Markdown track per feature under docs/features/. It complements issue trackers, specifications, and source code by linking the evidence that still matters rather than duplicating it.

When to Use This Skill

• Use when starting or resuming work on a feature after a session, agent, or tool change.
• Use when feature knowledge is scattered across PRDs, API notes, plans, issues, and old commits.
• Use when a long-lived feature needs durable decisions, risks, rollout constraints, or migration notes.
• Use when reviewing or finishing feature work and recording the verified outcome for future agents.
• Use when adopting lightweight project memory in an existing repository without reorganizing all documentation.

Do not use this skill merely to log every code edit or replace an existing issue tracker. Use it when future contributors need a concise, current view of an entire feature.

How It Works

Step 1: Discover Existing Feature Memory

Before changing a feature:

1. Read `docs/features/README.