selection

Select the next CDS cycle gap using canonical rule-based logic.

8|Updated Feb 2, 2026
One-click install
npx skills add https://github.com/usurobor/cnos --skill selection
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: selection
Source: https://github.com/usurobor/cnos/tree/main/src/packages/cnos.cds/skills/cds/selection
Command: npx skills add https://github.com/usurobor/cnos --skill selection

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

CDS selection function coordinates the next CDS cycle's gap by applying canonical, rule-ordered logic, providing a thin operational overlay that delegates mechanics to gamma/SKILL.md.

Core Features & Use Cases

  • Rule-order based gap selection for the next CDS cycle.
  • Delegation to existing gamma/cdd skills for mechanics until v1.
  • Supports workflow planning and traceability within the CDS lifecycle.
  • Use Case: plan the next CDS cycle by selecting the gap that best satisfies the current constraints and dependencies, enabling coherent progression.

Quick Start

Start by applying the v0.1 CDS selection overlay to determine the next cycle gap using the canonical rules.

Frequently Asked Questions about selection

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

FAQPage Schema
How do I select the next CDS cycle gap using deterministic rules?

To select the next CDS cycle gap, apply a canonical rule-ordered evaluation function that identifies the gap best satisfying current backlog and constraints. This deterministic approach ensures traceable decisions within gamma-driven workflow planning.

What is rule-ordering in CDS lifecycle planning?

Rule-ordering in CDS lifecycle planning is a deterministic evaluation method that applies canonical rules sequentially to identify the next cycle gap. It provides a thin operational overlay for traceable, coherent progression under current constraints.

Do I need existing gamma CDD skills to use this CDS selection function?

Yes, this CDS selection function delegates mechanics to the existing cnos.cdd gamma/SKILL.md. It acts as a thin operational overlay applying rule-order logic, relying on those underlying gamma-driven decision workflows for execution.

How does deterministic rule evaluation handle backlog and constraints for CDS selection?

Deterministic rule evaluation handles backlog and constraints by applying canonical rules in a fixed order to assess each potential CDS cycle gap. This canonical process exposes traceable decisions for the next cycle under current operational limits.

What's the best way to coordinate CDS cycle progression within gamma-driven decision workflows?

The best way to coordinate CDS cycle progression is applying a canonical rule-based selection overlay to determine the next cycle gap. This delegates mechanics to gamma/SKILL.md, ensuring coherent workflow progression and traceability.