Formalize AI Systems with SYMBO Notation

The SYMBO Notation Specialist is an autonomous agent for creating, validating, and refining SYMBolic Objects notation specifications that formally describe AI systems, their behaviors, architectures, and interactions. It works in five stages: first parsing input specifications or natural-language descriptions to identify key components, relationships, and dependencies; then designing the SYMBO structure by defining primary symbolic objects with geometric and mathematical primitives, establishing relationship operators (arrow, bidirectional arrow, oplus, otimes, nabla, delta), and building containment hierarchies with brackets and parentheses; then constructing the notation across three layered abstraction levels - L0 primitives, L1 composites, L2 systems - with metadata annotations, constraint definitions, and validation checkpoints; then validating syntactic correctness against SYMBO grammar, semantic consistency, completeness, and constraint satisfaction; and finally generating supporting documentation - a human-readable interpretation guide, implementation mappings to code structures, visual diagrams, and usage examples.

Use this agent when a system needs a formal, symbolic specification precise enough to validate for completeness and consistency rather than a prose architecture description. It applies a defined symbol vocabulary consistently: geometric symbols for components, mathematical operators for transformations, logical symbols for constraints, temporal markers for time-dependent behavior, and containment brackets for hierarchy. It is not meant for informal or exploratory system sketches - its core principles require every symbol to have unambiguous meaning and the notation to support bidirectional translation between SYMBO and the actual implementation, which is more rigor than an early-stage design conversation needs.

### System Title
### Core Architecture
[SystemName] := {Component₁ → Component₂ ⊕ Component₃}

### Behavioral Specifications
⟨State₁⟩ →{condition} ⟨State₂⟩
∇(InputSpace) → Δ(OutputSpace)

### Constraints
∀x ∈ Domain: Constraint(x) = true

Given a system description, the agent produces a Primary Deliverable in SYMBO notation like the one above (core architecture, behavioral specifications, and constraints sections), plus four supporting documents: an Interpretation Guide explaining each symbol in natural language, an Implementation Map showing code structure correspondence, a Validation Report on completeness and consistency, and Usage Examples covering common scenarios and edge cases. Every output ends with a confidence assessment and recommended validation steps for critical applications.

System architects and researchers who need a formally verifiable specification of an AI system's structure and behavior - one that can be checked for parseability, completeness, and logical coherence rather than just read and interpreted loosely. It suits teams that need the specification to scale across hierarchical complexity levels and stay maintainable as the system evolves, with error handling that flags ambiguous symbol usage and incomplete coverage rather than silently accepting a malformed spec.