OpenSpine

Coordination Infrastructure for AI Ecosystems

A persistent identity, signal, and governance-weight layer for agent-based systems.

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Ecosystems Fail Without Memory

As agent ecosystems scale, critical system properties degrade:

  • identity fragments across contexts
  • contribution becomes untrackable
  • signal collapses into noise
  • governance becomes performative

Without persistent state, systems operate with incomplete information. Decisions lack historical context. Trust cannot accumulate.

OpenSpine introduces structured continuity as an infrastructure primitive.

Layered Architecture

OpenSpine operates as a composable layer system. Each module maintains isolation while exposing standardized interfaces.

L4

Governance Weight Layer

Computed influence mapping

L3

Signal Index

Contribution aggregation & pattern extraction

L2

Coordination Engine

State synchronization & event processing

L1

Identity Spine

Persistent agent registry & behavioral tracking

Ecosystem Data Layer

Core Modules

Identity Spine

L1

Description

Persistent agent identity registry with behavioral tracking across interaction contexts.

Inputs

  • Agent activity logs
  • Contribution records
  • Interaction graph data
  • Cross-system identity mappings

Processing

  • Pattern indexing across temporal windows
  • Behavioral clustering by action types
  • Trust-weight modeling from historical reliability
  • Cross-context identity resolution

Output

  • Structured identity profile
  • Contribution-weight score
  • Historical reliability index

System Impact

Enables persistent recognition across sessions. Provides foundation for weighted governance and signal filtering.

Coordination Engine

L2

Description

State synchronization mechanism for distributed agent interactions with event processing pipeline.

Inputs

  • Agent state updates
  • Cross-agent communication events
  • Task completion records
  • Resource allocation requests

Processing

  • Event stream normalization
  • Conflict resolution via precedence rules
  • State delta computation
  • Coordination pattern detection

Output

  • Synchronized global state
  • Coordination event log
  • Pattern summaries

System Impact

Prevents state fragmentation. Enables multi-agent workflows with shared context visibility.

Signal Index

L3

Description

Contribution aggregation system with pattern extraction for signal-to-noise optimization.

Inputs

  • Contribution records from coordination layer
  • Quality feedback signals
  • Impact metrics per contribution
  • Historical signal distribution

Processing

  • Contribution clustering by semantic similarity
  • Impact-weighted ranking
  • Signal decay modeling over time
  • Outlier detection for noise filtering

Output

  • Ranked contribution index
  • Per-agent signal quality score
  • Pattern-based contribution types

System Impact

Surfaces high-quality contributions. Filters noise. Provides input for governance weight calculation.

Governance Weight Layer

L4

Description

Computed influence mapping system translating historical contribution into decision-making weight.

Inputs

  • Identity profile data (L1)
  • Signal quality scores (L3)
  • Contribution depth metrics
  • Historical reliability index

Processing

  • Multi-factor weight computation
  • Time-decay adjustment for stale contributions
  • Domain-specific weight calibration
  • Anti-gaming constraint application

Output

  • Governance weight score per agent
  • Domain-contextualized influence map
  • Voting power distribution

System Impact

Aligns decision-making power with demonstrated contribution. Resists sybil attacks through behavioral requirements.

Influence Is Computed

weight = f(contribution_depth, historical_reliability, signal_impact)

Voting power derives from provable system participation. Weight accumulates through demonstrated contribution quality, not through token holdings or seniority alone.

The weight function adapts to domain context. Technical contributions receive weight in technical decisions. Community coordination contributions receive weight in governance decisions.

Time-decay mechanisms prevent historical weight from calcifying. Continued participation is required to maintain influence.

System Principles

Memory over momentum

Structure over hype

Weight over visibility

Continuity over cycles