SSL Skill Normalizer

Purpose

This skill converts markdown-based skill artifacts into a structured Scheduling-Structural-Logical (SSL) representation as introduced in:

Liang et al., "From Skill Text to Skill Structure: The Scheduling-Structural-Logical Representation for Agent Skills", arXiv:2604.24026 (2026).

SSL addresses the core limitation of free-form skill text: it is human-readable but hard for agents to reason over, discover, and audit. By mapping each skill into three complementary layers, SSL makes skills searchable (improved MRR 0.573 → 0.707 in the paper) and risk-assessable (improved macro F1 0.744 → 0.787).

The Three SSL Layers

The representation is grounded in Schank & Abelson's theories of Memory Organization Packets (MOPs), Script Theory, and Conceptual Dependency. Each layer captures a different dimension of skill knowledge:

Layer 1 — Scheduling (When / Who)

Answers: When should this skill be invoked? By whom, given which inputs and outputs?