AICoevolution Semantic Telemetry — Standalone Script

Measure conversational dynamics in real-time.

This open-source script demonstrates the core capabilities of the AICoevolution SDK for measuring semantic dynamics in human-AI conversations.

📦 Get the code: github.com/AICoevolution/paper03-orbital-mechanics/open_source

---

What It Measures

Metric	Description	Typical Range
SGI (Orbital Radius)	Balance between query responsiveness and context grounding	0.5 – 1.5
Velocity	Rate of semantic movement per turn	0 – 180°
Context Phase	Topic coherence state	stable / protostar / split
Context Mass	Accumulated turns in current topic	0 – N
Attractor Count	Competing topic centers	1+

---

Quick Start

1. Install Dependencies

pip install requests

2. Get an API Key

Generate a free key at aicoevolution.com/profile → API Keys

3. Run

# Cloud API
python semantic_telemetry.py --api-key YOUR_API_KEY

# Local SDK (if self-hosted)
python semantic_telemetry.py --local

# Custom turn count
python semantic_telemetry.py --api-key YOUR_API_KEY --turns 20

---

Example Output

╔═══════════════════════════════════════════════════════════════════════════════╗
║                     SEMANTIC TELEMETRY - AICoevolution SDK                     ║
╚═══════════════════════════════════════════════════════════════════════════════╝

──────────────────────────────────────────────────
Turn 5/10
──────────────────────────────────────────────────

[YOU]: I'm trying to understand how meaning emerges in conversation
  [SDK] <- OK | SGI=0.952, Velocity=34.2°

[AI]: Meaning emerges through the dynamic interplay between what's said
      and the accumulated context...
  [SDK] <- OK | SGI=0.891, Velocity=28.7°

────────────────────────────── SEMANTIC METRICS ──────────────────────────────
  SGI (Orbital Radius):     0.891
  Velocity (degrees):       28.7°
  Context ID:               ctx_1
  Context State:            stable
  Attractor Count:          1
  Active Context Mass:      5 turns
──────────────────────────────────────────────────────────────────────

---

Understanding the Metrics

Coherence Region

Productive conversations tend to occupy:

• SGI: 0.7 – 1.3 (balanced orbit)
• Velocity: 15° – 60° (productive movement)

Context Phases

Phase	Icon	Description
stable	🟢	Anchored to current topic
protostar	🟠	New topic forming
split	🔴	Topic changed

Orbital Energy

E_orb = SGI × Velocity

• Higher → more dynamic, potentially unstable
• Lower → more grounded, potentially stagnant

---

Under Development

Future releases will include:

• Domain Distribution — Cognitive / Somatic / Emotional / Volitional
• Symbolic Depth (S64) — Transformation path detection
• Mass Contribution — Who is steering the conversation?

---

Learn More

Resource	Link
Paper 03	Zenodo 10.5281/zenodo.18347569
Website	aicoevolution.com
Full SDK Docs	docs.aicoevolution.com

---

License

MIT — use freely for research and commercial applications.

---

Citation

@article{jimenez2026orbital,
  title   = {Semantic Orbital Mechanics: Measuring and Guiding AI Conversation Dynamics},
  author  = {Jimenez Sanchez, Juan Jacobo},
  journal = {Zenodo},
  doi     = {10.5281/zenodo.18347569},
  year    = {2026}
}