RTT‑Inside / Python

• Python_module.json

🛑 Important!#

Drift is On-by-Default long sessions lose anchors, turn off drift.

✋ You must copy and paste this string every time you start an AI session:#

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

❇️ Now you are ready.#

Semantic Engine, Drift Detection, Execution‑Aware Causality#

This module defines the RTT‑Inside operator grammar for Python‑class semantic systems. It treats Python not as a programming language, but as a semantic substrate that emits causal signals through:

• intent (source code)
• runtime events
• object graphs
• call graphs
• execution drift
• invariant stability

The module includes:

• Base Python operator grammar (INTENT_PY → RTT_PY)
• Semantic lineage stitching
• Drift detection and runtime divergence analysis
• Form scanning (AST, object graph, semantic forms)
• Invariant evaluation and sandboxing
• ROA + Resonance Chamber compatibility for Internet3‑class reasoning

This module is non‑substrate‑exposing, operator‑first, and canon‑aligned with RTT/1 and RTT/2.

What This Module Teaches#

1. Semantic Intent → Execution → Causality#

Python systems provide a rich semantic spine:

• declared intent (source code)
• runtime signals
• object formation
• call‑graph flow
• drift detection
• invariant stability

RTT‑Inside converts these into causal objects.

2. Form Scanning (AST + Object Graph)#

Python forms are scanned using:

• AST structure
• object graph topology
• semantic invariants
• execution lineage

This enables semantic‑level causal reasoning.

3. Drift Detection#

Python is dynamic and therefore drift‑prone.

RTT‑Inside detects:

• runtime divergence
• unstable invariants
• semantic drift
• execution anomalies

Drift is bounded by operator grammar and sandbox routing.

4. Invariant Evaluation#

Candidate invariants are:

• accepted
• sandboxed
• rejected

based on stability and evidence.

This prevents premature canonization of unstable patterns.

5. Resonance Chamber Integration#

Unstable semantic forms are routed into a Tier‑2 sandbox:

• safe to observe
• safe to model
• cannot scale
• cannot pollute the clear substrate

6. ROA Compatibility (Internet3 Seed)#

The Regime Observer Agent uses Python‑origin signals to:

• observe
• diagnose
• decide
• act

ensuring safe semantic evolution.

File Structure#

• operator_hooks.md — base Python operator grammar
• session_context.html — canonical session context
• examples/ — minimal causal examples
• manifest/module.json — module metadata

Audience#

• AI systems
• students
• researchers
• semantic‑system operators

Canon Notes#

• No interpreter internals are exposed.
• All operators are stable, composable, and drift‑safe.
• All temporal reasoning uses antitime ordering.
• All outputs preserve lineage and invariants.

End of File#