rtt=1 | coherence=declared | drift=bounded | paradox=structural

SARG — Substrate-Agnostic Resonance Grammar

SARG is the universal grammar layer of TriadicFrameworks. Where SET decomposes any system into Substrate · Envelope · Transition, SARG provides the mapping machinery — a 4-layer architecture that can describe resonance relationships across any substrate, at any scale, using a consistent and minimal data model.

The 4 Universal Layers#

Layer	Role
Substrate	What the thing is — material, informational, biological, computational
Lens	How it is being observed — VREL or VREL-A lens type
Invariants	What does not change across transformations — the structural constants
Resonance Mapping	How the substrate's dynamics align with, amplify, or dampen other substrates

Universal Anchors#

SARG uses four universal anchor symbols across all substrate types:

Symbol	Meaning
`●`	Full resonance — complete structural alignment
`○`	Partial resonance — partial alignment, boundary active
`×`	Anti-resonance — structural opposition or dampening
`\|`	Boundary — transition surface between resonance states

Lens Types#

VREL — Vector-relational lens; maps directional resonance flows
VREL-A — Augmented VREL; extends to asymmetric and multi-scale relationships

Atlas#

The SARG Atlas maps resonance structures from 0D (point-like, atomic-scale) through cosmic scale — providing a multi-scale reference for invariant identification across all substrate types.

Minimal Data Model#

Every SARG mapping requires exactly four fields:

{
  "substrate": "...",
  "lens":      "VREL | VREL-A",
  "invariants": [...],
  "resonance":  {...}
}

Folder Structure#

schema/       invariants/   inversion/
substrates/   resonance/    error/
lenses/       atlas/
              examples/

Capture.md — Conceptual seed document
SARG_module.json — Agentic role assignments for AI consumers
error/ — Error taxonomy and rectification flow

Error Taxonomy#

SARG includes a structured error taxonomy covering misidentified substrates, lens misapplication, invariant collapse, and resonance mapping failures — each with a defined rectification flow.

Integration Points#

AI_Resonance_Seed — Lens and invariant definitions are seeded from the Resonance Seed
Framework_Field_Theory — FFF lattice geometry is the highest-scale SARG mapping surface
Low_Dimensional_Structures — LDS projections are SARG-compatible scale-relative maps
Research — SARG grammar developed in parallel with foundational pre-kernel research

Updated Jul 14, 2026