Concrete artifacts you can read in under a minute — no install required for the static examples; offline CLI for a live receipt.
Source: examples/receipts/golden/brainrot-aura.json
| Field | Value |
|---|---|
| Query (ingest) | brainrot aura farming mid cooked |
| Lineage family | brainrot-aura |
| Matched terms | brainrot, aura, aura farming, mid, cooked, let him cook |
| Confidence | 0.98 · provenance INFERRED |
| Receipt integrity | e8e43b010371 |
| Brier | null (open analysis — not settled) |
Observed (excerpt): Mock memetic channel on brainrot / aura farming vocabulary with status-radiation payload (content degradation + identity signaling).
What you may claim: this query matches the brainrot-aura lineage family with high lexical confidence under the offline registry.
What you must not claim: a numeric Brier or “50% chance this goes viral” from the open receipt alone.
Open constellation · family brainrot-aura →
??? note "Open golden receipt JSON (excerpt)" Full file in the repo. Core shape:
```json
{
"ingest": { "query": "brainrot aura farming mid cooked" },
"analysis": {
"lineage": {
"family_id": "brainrot-aura",
"matched_terms": ["brainrot", "aura", "aura farming", "mid", "cooked", "let him cook"],
"confidence": 0.98,
"provenance": "INFERRED"
}
},
"provenance": { "brier": null },
"receipt": { "integrity": "e8e43b010371" }
}
```
backfill-ytd-2026-analysis — 16 receipt summaries, multi-family distribution, publish-safe Pages history.
python3 scripts/hyperlex.py demo --query "rizz"Writes a receipt and prints a compact result packet with brier: null.
Case studies · e2e mock scan under examples/case-studies/.