Coming soon
Awareness JSONs
A data format for tracking the Awareness Equation in real life.
Key Objective: Define a practical schema ("Awareness JSON") that captures state: Blockers, Purity, Shakti, Belief, plus notes + context + timestamps.
TL;DR
- Awareness JSON = a schema for tracking the Awareness Equation in real life.
- Required keys: belief, blockers[], purity, shakti, context, timestamp, notes.
- Optional keys: triggers, bodySignals, practicesTried, outcome, confidence.
- Functions as logs, observability, state snapshots, diffing.
- Privacy + safety: sensitive personal data — handle carefully.
Why we need a schema (from philosophy → debugging)
Part I–VI established the Awareness Equation as a model. But models are useless without data. How do you track variables in real life? How do you measure Blockers, Purity, Shakti, Belief? You need a schema.
Awareness JSON provides that schema. It's a data format that captures state snapshots. Like a log file: record state at time T, compare to state at time T+1, identify patterns.
This is not medical data. This is personal debugging data. Use it to track patterns, not to diagnose.
The schema (show a JSON example)
Required keys:
{
"timestamp": "2026-01-15T10:30:00Z",
"belief": {
"total": 0.7,
"b1": 0.8,
"b2": 0.6,
"mode": 1,
"floorEpsilon": 0.01
},
"blockers": [
{
"type": "fear",
"intensity": 0.6,
"trigger": "work deadline",
"notes": "feeling overwhelmed"
}
],
"purity": 0.5,
"shakti": 0.4,
"context": "morning, before work",
"notes": "feeling low energy, some fear about deadline"
}Optional keys:
- triggers: What triggered this state? (events, people, situations)
- bodySignals: Physical sensations (tension, energy, clarity)
- practicesTried: What did you try? (meditation, exercise, rest)
- outcome: What happened? (state improved, worsened, stayed same)
- confidence: How confident are you in these measurements? (0-1)
Engineering Translation
- Logs: Awareness JSON = log entries. Record state at regular intervals. Like application logs: timestamp + state + context.
- Observability: JSON enables observability. You can query: "show me all states where blockers > 0.7" or "show me patterns during morning vs evening."
- State snapshots: Each JSON = one snapshot. Compare snapshots over time to see patterns. Like git commits: each commit is a snapshot.
- Diffing: Compare JSON T vs JSON T+1. What changed? Blockers increased? Purity decreased? This is diffing: identify deltas.
Example walkthrough (one filled example + interpretation)
Example JSON:
{
"timestamp": "2026-01-15T14:00:00Z",
"belief": {
"total": 0.3,
"b1": 0.7,
"b2": 0.2,
"mode": -1,
"floorEpsilon": 0.01
},
"blockers": [
{
"type": "fear",
"intensity": 0.8,
"trigger": "work deadline",
"notes": "panic about deadline, can't focus"
},
{
"type": "shame",
"intensity": 0.5,
"trigger": "feeling behind",
"notes": "self-criticism"
}
],
"purity": 0.3,
"shakti": 0.2,
"context": "afternoon, work stress",
"triggers": ["deadline", "boss email"],
"bodySignals": ["tension in shoulders", "low energy"],
"practicesTried": ["breath work", "didn't help"],
"outcome": "state worsened",
"confidence": 0.7,
"notes": "feeling overwhelmed, belief dropped to -1 mode"
}Interpretation:
- Belief: Mode −1 (adversarial). B1 (0.7) ≠ B2 (0.2) = low coherence. This suggests intellectual agreement but operational disbelief.
- Blockers: High (fear 0.8, shame 0.5). Multiple blockers active.
- Purity: Low (0.3). Low stability.
- Shakti: Low (0.2). Low energy.
- Pattern: Work stress → blockers increase → belief drops → purity/shakti drop. This is a cascade: one variable drops, others follow.
- Intervention: Reduce intensity (lower work stress), increase stability (purity), re-anchor to one principle (breath), reframe using Belief (this is integration, not failure).
Privacy + safety notes (sensitive personal data)
⚠️ Privacy warning:
- Awareness JSON contains sensitive personal data (mental state, triggers, practices).
- Store securely. Encrypt if storing in cloud. Don't share without consent.
- This is not medical data, but it's still sensitive. Treat it like a diary.
Safety notes:
- This is debugging data, not diagnosis. Don't use it to self-diagnose.
- If you notice severe patterns (persistent Mode −1, high blockers, low purity), consider seeking qualified help.
- This is a tool, not a replacement for therapy or medical care.
References (primary sources)
This is a research notebook, not medical or therapy advice. Safety guidelines →