GH GambleHub

Ecosystem Activity Index

1) Why do we need a single index

There are many metrics in a complex network and they conflict (growth of DA traffic when quality drops, revenue when SLO is degraded). The Ecosystem Activity Index (IAE) is a consensus composite that:
  • gives one figure for governance and public reporting;
  • decomposed into sub-indexes for actions for reasons, not symptoms;
  • Linked to triggers (auto-change of tariffs/quotas/bonuses)
  • resistant to noise, seasonality and cheating.

2) Index architecture (top level)

IAE is built from five sub-indices:

1. CAI - Core Activity Index (basic activity): unique active subjects, cross-chain messages, finalized tx, DA publications, MAU/WAU, active RNFT.

2. GMI - Growth Momentum Index: MoM/WoW acceleration by key metrics, onboarding ratios, conversion from visits to actions.

3. QTI - Quality & Trust Index: SLO success, p95 latency, dispute share, curation accuracy, security incidents, R-token reputation.

4. MEI - Monetization Efficiency Index (economics): ARPU/ARPPU, NRR/GRR, Cost-to-Serve/request, margin/message, share of repeated revenue, distribution fairness.

5. SSI - Sustainability & Safety Index: MTTR, redundancy, tail amplification (p99/p50), share of slashes, egress anomalies, concentration of influence (Gini).

IAE = weighted mean of sub-indices after normalization.

3) Metrics (reference list)

3. 1 Core (CAI)

Unique active subjects (daily/weekly/monthly) .
Cross-domain messages/day; finalised transactions.
DA bytes/publications; Active RNFT contracts share of completed quests/missions.

3. 2 Growth (GMI)

Onboarding (new DIDs/contracts), D1/D7 activation.

Supply/demand sozdateli→potrebiteli

Elasticity: ∂trafik/∂tsena (reaction to tariff changes).

3. 3 Quality & Trust (QTI)

SLO success by QoS class (Q4/Q3/Q2/Q1).
p95/p99 latency; duplicate ratio; out-of-order %.
Accuracy of curation (precision/recall), share of disputes, win-rate oracles.
R-distribution (median/quartiles), proportion of sanctions/amnesties.

3. 4 Monetization (MEI)

ARPU/ARPPU, NRR/GRR, CAC/Payback, margin/message.
Cost-to-Serve (CPU/GPU/DA/egress), cache efficiency.
Share of revenue protected by collateral S; RevShare by role.

3. 5 Sustainability & Safety (SSI)

MTBF/MTTR, error budget burn, flap-rate of the balancer.
Tail Amplification = p99/p50; capacity headroom.
Slashing rate/1000 events; the proportion of compliance locks.
Gini index by vote/income; entropy of revenue sources.

4) Normalization and aggregation

4. 1 Data preparation

Depersonalization and ZK proofs for compliance metrics (minimum PD).
Dedup/idempotency (ULID/trace-id).
Tail winsorization (1-2 percentile) for emission resistance.
Seasonal decomposition (STL) and EWMA smoothing.

4. 2 Normalization

For each metric (m):
  • Robust z-score: (z = (m -\text {median} )/\text {MAD})
  • Or min-max robust on percentiles [P5, P95].

4. 3 Weights and composite

Sub-index (S_k =\sum w_{k,i},\hat m_{k,i}).

Master Index:
[
\text{IAE} = \sum_{k \in {CAI,GMI,QTI,MEI,SSI}} W_k \cdot S_k
]

Weights (W_k) and (w_{k,i}) utverzhdayutsya治理, stored in the Governance Registry, change according to the sunset procedure.
Constraints: (\sum W_k = 1,; W_k \in [0. 1, 0. 35]) to diversify.

5) Anti-gaming and honesty

Blind-run window: some data is hidden until the report is published.
Control tasks/" honey traffic" to identify pharming.
Behavioral signatures and anomaly-detection (channel correlations).
Penalties: S-slashing for deliberate markups, R-fines, nullification of the campaign sub-index.
"Blacklist" tactics; public post-mortems.

6) policy hooks

SLO switches: QTI <threshold → reduction of Q0/Q1 quotas, Q4 priority gain.
Tariffs: MEI↓ at stable QTI → auto-reduction take rate (in koridore治理) for quality domains.
Risks: SSI <threshold → inclusion of stop cranes/circuit-breakers, growth of collateral S.
Growth: GMI≥X at QTI/SSI normally → grants/incentive pools (treasury).
Compliance: a surge in locks → auto-hard fail-closed by geo/segment.

7) Dashboards and cuts

IAE Overview: index, WoW/MoM delta, contribution of sub-indices.
Roots & Levers: contribution of metrics to sub-indices, elasticity to weights.
Tail Heatmap: p95/p99 by domain/route; TailAmplification.
Economy Panel: ARPU/NRR/Cost-to-Serve/маржа.
Trust & Safety: disputes, slashings, compliance blocks, fraud rate.
Geo/Segment: cross-section by region/role (creators, nodes, affiliates, operators).

8) Report format and calendar

Cadence: Weekly Summary + Monthly Drilldown + Quarterly Public.
Release passport: versions of scales, diagrams, sources, methodology, blind-run windows.
SLO table: pass/fail by key metrics and actions.
Economics: MEI total and Treasury stimulus/insurance budget.
Risks/incidents: list, MTTR, corrections, impact on SSI.

9) Link to RNFT contracts and roles

RNFT rights can include target sub-indexes; non-fulfillment → penalty/cliff.
R-reputation affects the weights of quality and voice signals by index weights.
S-pledge covers compensation for fraud/incidents, reflected in SSI/MEI.

10) Thresholds (landmarks)

IAE ≥ 0. 65 (on a robust scale of 0.. 1) → green zone, growth with increasing quotas.

0. 45–0. 65 → neutral: point tuning of tariffs/quotas.

🚨 0. 45 → red zone: resource saving regime, revision of incentives, strengthening anti-fraud.

Hard sub-index thresholds (e.g. QTI <0. 5 or SSI <0. 5) can block growth and turn on stopcocks independently of IAE.

11) Implementation playbook

1. Value decomposition: flow maps (people/nodes/content/liquidity).
2. Selection of metrics: by CAI/GMI/QTI/MEI/SSI blocks; identification of sources.
3. ETL/data quality: dedup, idempotency, anonymization/ZK, integrity tests.
4. Normalization and weights: selection of robust scales, initial (W_k), sunset procedures.
5. Anti-gaming: control tasks, blind-run, anomaly-detection.
6. Dashboards and SLO-gates: visualization, alerts, error budgets.
7. Pilot: 1-2 quarters on selected domains, comparison with business KPIs.
8. 治理: record the process of changing weights, revisions, public reports.
9. Trigger automation: integration with tariffs/quotas/stopcocks.
10. Retrospective: analysis of the impact of the index on decisions and P & L.

12) Delivery checklist

  • Sub-indexes and metrics defined, data sources agreed
  • Implemented normalization (robust z/robust min-max) and EWMA
  • Configured governance weights with sunset and audit changes
  • Enabled anti-gaming measures and blind-run windows
  • There are deposit dashboards and automatic action triggers
  • Report passport and publication calendar described
  • RNFT rights/penalties associated with sub-indexes
  • Pilot performed and weights adjusted based on results

13) Glossary

IAE: The main activity/health composite of the ecosystem.
CAI/GMI/QTI/MEI/SSI: sub-indices of core, growth, quality/trust, monetization, sustainability.
Tail Amplification: p99/p50 ratio - tail strength of delays/risks.
Robust z/min-max: emission-resistant normalizations.
Sunset procedure: temporary change of weights/thresholds with auto-rollback.
Blind-run: Hidden run of metrics against markups.

14) The bottom line

The ecosystem activity index turns disparate indicators into an operational compass. It gives a simple public guideline, but retains depth for actions: through sub-indices, triggers i治理 -weight control. With correct normalization, protection against markups and bundling with RNFT stimuli, IAE helps to grow the network quickly, transparently and safely, without sacrificing quality and stability.

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