skills.rest
aurora-atoms
aurora-atomsCOMMUNITY
Explore all skills by this author →
GitHub

feature-understanding-loop

Coordinate feature delivery cases into reviewable states via evidence-based modeling.

Updated Jun 1, 2026
Search Tags:#governance#risk-management#evidence-based#feature-delivery#system-modeling#delivery-readiness
One-click install
npx skills add https://github.com/aurora-atoms/lattice --skill feature-understanding-loop
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: feature-understanding-loop
Source: https://github.com/aurora-atoms/lattice/tree/main/skills/feature-understanding-loop
Command: npx skills add https://github.com/aurora-atoms/lattice --skill feature-understanding-loop

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill solves the problem of fragmented, unverified, or speculative feature understanding by enforcing an evidence-based loop that moves a feature delivery case toward a reviewable state.

Core Features & Use Cases

  • Evidence-Grounded Modeling: Builds a system slice and claim ledger based on verified sources rather than assumptions.
  • Adversarial Challenge: Actively seeks contradictions, stale assumptions, and hidden dependencies to ensure robustness.
  • Use Case: Use this when a team is kicking off a complex brownfield feature and needs to ensure that all critical controls, acceptance criteria, and impact boundaries are verified before implementation begins.

Quick Start

Use the feature-understanding-loop skill to initialize a new understanding contract for the provided feature delivery case and identify the next required decision gate.

Frequently Asked Questions about feature-understanding-loop

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

FAQPage Schema
How do I verify feature delivery readiness before implementation?▼

Feature delivery readiness is verified by building an evidence-based system slice and claim ledger from verified sources, actively challenging assumptions, and ensuring all acceptance criteria are reviewable before implementation begins.

What is evidence-grounded feature modeling for brownfield systems?▼

Evidence-grounded feature modeling is the process of constructing system slices and domain rules strictly from verified sources rather than assumptions, ensuring fragmented knowledge is transformed into a reviewable delivery state.

How do I identify hidden dependencies and stale assumptions in complex feature delivery?▼

You identify hidden dependencies and stale assumptions by applying adversarial challenge techniques to your feature-specific system slices, actively seeking contradictions to ensure robust delivery integrity.

Can I use source-supported verification for brownfield feature delivery?▼

Yes, source-supported verification is required for brownfield feature delivery, enforcing teach-back validation and append-only delta recording to maintain strict integrity during the transition to a reviewable state.

When do I need an adversarial challenge loop for feature understanding?▼

You need an adversarial challenge loop when kicking off a complex brownfield feature, ensuring critical controls, impact boundaries, and acceptance criteria are fully verified before implementation or PR review.

Does feature delivery governance work without strict claim ledgers?▼

Feature delivery governance requires strict claim ledgers to maintain delivery integrity, using append-only delta recording and teach-back validation to prevent speculative or unverified assumptions from entering the system model.

Related Skills

Explore More Software Engineering Skills→
AndVl1AndVl1
4

compose-arch

Enforces Screen/View/Component layered architecture for Compose Multiplatform projects.

Community
Advanced
guifryguifry

ralph-review

Automates per-story code review and PR readiness reporting for Ralph-generated commits.

Community
Advanced
HeadyAIHeadyAI
1

heady-governance-atlas

Maps regulations, manages policies, and enforces governance for AI systems.

Official
Advanced
aurora-atomsaurora-atoms

delivery-readiness-card

Aggregate ticket, PR, and test evidence into readiness cards with gaps and next actions.

Community
Advanced