trails-derive-from-source

Align Trails changes with authoritative owner exports to prevent shadow data.

4|1|Updated Mar 28, 2026
One-click install
npx skills add https://github.com/outfitter-dev/trails --skill trails-derive-from-source
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: trails-derive-from-source
Source: https://github.com/outfitter-dev/trails/tree/main/plugin/skills/trails-derive-from-source
Command: npx skills add https://github.com/outfitter-dev/trails --skill trails-derive-from-source

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Proposals that derive framework facts, projections, or surface metadata can rely on non-authoritative sources, creating shadow data, duplication, and indirection. This skill guides teams to locate the rightful owner exports and align downstream consumers with a canonical source.

Core Features & Use Cases

  • Owner-first alignment: identify the natural owner module for a fact and verify it exports typed data.
  • Shadow-data reduction: prefer owner exports over local projections to minimize duplication and confusion.
  • Governance workflow: document steps to escalate to the owner package when ownership is unclear or missing.
  • Use cases: when introducing new error classes, intents, projections, or metadata maps that affect multiple surfaces.

Quick Start

Provide a change proposal and invoke the derive-from-source workflow to confirm a single authoritative owner export.

Frequently Asked Questions about trails-derive-from-source

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

FAQPage Schema
How do I prevent shadow data when introducing new projections or metadata maps?

To prevent shadow data when introducing projections or metadata maps, identify the natural owner module and verify it exports typed data before aligning downstream consumers with that canonical source.

What is a canonical source in framework fact derivation?

A canonical source is the authoritative owner export that provides typed data for framework facts, ensuring downstream surfaces avoid duplication and indirection caused by relying on non-authoritative local projections.

How do I align downstream consumers with an owner export?

Align downstream consumers by invoking a derive-from-source workflow with your change proposal, confirming a single authoritative owner export exists and is discoverable before creating local lists or projections.

When should I escalate to the owner package during framework fact derivation?

You should escalate to the owner package during framework fact derivation when ownership of a fact is unclear or missing, ensuring the rightful owner module exports typed data before you proceed.

Does deriving framework facts from a canonical source work with Warden rules?

Yes, deriving framework facts from a canonical source applies to changes that introduce Warden rules across core packages, requiring owner module exports to be discoverable and preferring narrow owner exports.

Why do local projections create shadow data in core packages?

Local projections create shadow data in core packages because they rely on non-authoritative sources, causing duplication and confusion instead of aligning downstream consumers with a single canonical owner export.