Steer Skill Authoring

What problem does it solve?

Prevents multiple AI agents and sessions from interpreting scenario priorities differently by shaping consistent mental models and convergence patterns for steer-style guidance.

Core Features & Use Cases

• Shared mental models: Frames the problem so any agent will reach the same architectural decisions, keeping DRY and preventing divergent implementations across sessions.
• Convergence patterns: Uses decision trees, tables, and layered diagrams to remove ambiguity from multi-step choices and governance discussions.
• Scope and output expectations: Defines what is in/out of scope, audit requirements, protective comments, and the memory loop so agents know exactly where to read, what to change, and what to document.
• Use case: When updating scenarios/{{TARGET}}, follow these principles to document findings, harden focus statements, and steer the scenario development loop toward consistent outcomes.

Quick Start

Start by reviewing existing scenario findings, craft a focus statement with {{TARGET}} placeholders, and record your discoveries before ending the session so the memory loop stays intact.