jordan 1ce4004807 feat: Complete Phase 2 (The Cortex) - query, lens, and API layers

This commit adds the read path (Cortex) to complement the write path (Spine):

## Crates
- stemedb-api: HTTP API with axum + utoipa OpenAPI
  - /v1/assert, /v1/query, /v1/epoch, /v1/skeptic, /v1/trace, /v1/audit
  - Metered endpoints with quota enforcement
  - Ed25519 signature verification
- stemedb-lens: Truth resolution lenses
  - RecencyLens, ConsensusLens, ConfidenceLens
  - VoteAwareConsensusLens (Ballot Box pattern)
  - TrustAwareAuthorityLens (The Hive pattern)
  - SkepticLens (conflict analysis)
  - EpochAwareLens (paradigm-safe queries)
- stemedb-query: Query engine with materialized views

## Storage Extensions
- VoteStore: Vote aggregation with cached counts
- TrustRankStore: Agent reputation with decay
- AuditStore: Query audit trail
- IndexStore: SP/P/S index structures
- SupersessionStore: Epoch supersession chains

## SDKs
- sdk/go/steme: Go HTTP client with Ed25519 signing
- sdk/go/adk: ADK-Go tools for AI agents

## Documentation
- Updated CLAUDE.md, architecture.md, roadmap.md
- New ai-lookup entries for all services
- Use case docs for consumer health intelligence
- Arena roadmap for simulation advancement

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>

2026-02-01 13:22:44 -07:00

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Simulation System ("The Arena")

Last Updated: 2026-01-31 Confidence: High Status: Phase 1 Complete (Spine validation)

Summary

The Simulation is an Agent-Based Modeling (ABM) environment that validates StemeDB under emergent, adversarial, and evolutionary pressure. It simulates a society of AI agents with conflicting goals living within the knowledge graph.

Key Facts:

Codename: "The Arena"
Purpose: Integration testing via societal stress tests, not unit tests
Architecture: stemedb-sim binary orchestrating agent swarms via tokio
Agents communicate only through StemeDB reads/writes

File Pointers:

Implementation: crates/stemedb-sim/src/main.rs
Vision document: /simulation-vision.md
Incremental roadmap: /arena-roadmap.md

Agent Personas

Persona	Goal	Behavior
Scientist	Converge on truth	High-confidence assertions, cites sources
Troll	Sow chaos	Low-confidence contradictions, frequent forks
Believer	Amplify consensus	Trusts high-reputation agents
Skeptic	Find variance	Reduces confidence of unverified claims
Historian	Preserve context	Resurrects dormant truths with new evidence

The Gameplay Loop

Assertion: Agent reads ground truth, creates assertion
Fork: Adversarial agent forks reality with contradiction
Lens Resolution: Query agent applies Lens (e.g., Consensus)
Reputation Update: TrustRank adjusts agent reputations
Decay: Unverified assertions fade via Dormancy Protocol

Success Criteria

Truth survives: High-reputation assertions outlive spam
Lenses work: Consensus lens filters Troll noise
Performance: 1000 concurrent agents without locking
Emergence: Trust clusters form without hardcoded rules

Metrics

Tracked via Prometheus/Grafana:

global_truth_convergence - Entropy of the graph
agent_reputation_distribution - Reputation spread
fork_depth_max - Deepest branch depth

Current Status

The simulator currently validates Phase 1: The Spine (WAL + Ingestor + KV Store). It proves the write path works end-to-end with signature verification.

What's implemented:

3 agents (2 Scientists, 1 Troll)
10 ticks of assertion creation
Ed25519 signature verification
WAL → Ingestor → KV Store pipeline

What's NOT implemented yet:

Query path (uses direct KV access, not QueryEngine)
Voting and consensus
TrustRank reputation
Concurrent agents
Agent persona differentiation

Roadmap

See arena-roadmap.md for the incremental path from current state to full ABM environment.

TrustRank - Reputation algorithm
Branching - Fork mechanics
Lens System - Query resolution

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