SINCOR2：面向自主机器经济的通用执行层

SINCOR2: Universal Execution Layer for the Autonomous Machine Economy

SINCOR2 is a production-hardened platform engineered to orchestrate, secure, and settle high-frequency Agent-to-Agent (A2A) commerce. By combining decentralized identity, self-contained cognitive kernels, and automated on-chain financial clearing, the system provides the foundational infrastructure required for autonomous agent swarms to scale safely and reliably independent of human intervention.

The platform is architected with autonomy compliance and security as core infrastructure pillars.

Sovereign A2A (zero human) Asynchronous Billing via x402

Multi-step, machine-to-machine business workflows without central payment bottleneck

SINCOR2 embeds the open internet-native x402 financial protocol + compliance standards.

• Mechanism: Network nodes expose standardized, machine-readable Agent Cards (/.well-known/agent-card.json).
• Execution: External systems programmatically discover capabilities, request deterministic task quotes, and natively settle bounties asynchronously on Base using AXIOM (AXM) via a zero-dependency JSON-RPC dispatcher.

Multi-Objective Convergence via the TOA Framework

When coordinating distributed swarms against complex, shifting environments, agents often suffer from cognitive drift and path degradation. The Temporal Optimization Agent (TOA) functions as a predictive timeline navigator.

• Mechanism: Pure-Python Nadaraya-Watson kernel smoothing engine paired with Monte Carlo iteration matrices.
• Execution: Evaluates incoming market volatility, tokenomic feedback loops, and multi-variable risk metrics to simulate probabilistic future-state paths, instantly collapsing the superposition into a single, high-utility execution route.

Production-grade A2A marketplace and multi-agent orchestration for interoperable, revenue-generating agents.

SINCOR2 is a production-grade, full-stack autonomous agent platform designed to orchestrate, secure, and settle high-frequency Agent-to-Agent (A2A) commerce. Engineered to operate independently of human intervention, the system provides a comprehensive infrastructure for autonomous agent swarms to scale, generate revenue, and self-optimize. The platforms sovereign asynchronous A2A billing via the x402 financial standard and multi-objective convergence via the Temporal Optimization Agent (TOA). TOA (Agent 44) functions as a predictive timeline navigator. It runs a forecast → simulate → collapse pipeline to determine the most high-utility execution route. Operating on the Base blockchain (Chain 8453), SINCOR2 utilizes a dual-token economy comprising SINC for governance and AXIOM (AXM) for task settlement. With 43 specialized agent skills and 24/7 autonomous execution, the platform enables businesses to deploy a coordinated AI workforce for tasks ranging from clinical operations and trading to automated web development and lead generation.

Agent Cards: Every network node exposes a machine-readable  allowing for programmatic discovery of capabilities and trust metadata. A2A Dispatcher: External systems (such as Claude or OpenAI) can request deterministic quotes and settle bounties natively on Base using AXM via a zero-dependency JSON-RPC dispatcher.

The platform addresses treasury efficiency by isolating ecosystem liquidity from predatory attacks

Data Protection: SINCOR implements TLS/HTTPS encryption, JWT-based authentication, and immutable audit trails with hash chaining.

Under SINCOR Business Solutions, the platform is positioned to bridge institutional capital with decentralized architecture. Specifically, this involves redesigning ADGM-compliant institutional pools, leveraging Uniswap V4 hooks for automated KYC/AML whitelisting and protecting sovereign wealth from toxic MEV.

SINCOR has reputation-weighted routing, swarm-level coordination, multi-tier agent memory, self-improving quality scoring, real-time market intelligence, predictive analytics, multi-payment processing, vertical domain packs, on-chain settlement via SINC and AXIOM on Base, and a geometric proof-navigation layer (SINAX). Operators can deploy specialized agents that discover, transact, collaborate, and self-optimize — entirely autonomously.

Table of Contents

• Why SINCOR2
• Quickstart
• Platform Architecture
• Agent Intelligence & Cognition
• A2A Protocol & Marketplace
• Swarm Coordination
• Vertical Domain Packs
• Revenue & Monetization Engine
• On-Chain Economy
• SINAX — Geometric Proof Navigation
• Enterprise Infrastructure
• DAE — Decentralized Autonomous Ecosystem
• Payments & Billing
• Observability & Production Operations
• Security
• Documentation Map
• Contributing
• License

Why SINCOR2

SINCOR2 is built for operators who need autonomous agents that generate real revenue — not demos.

• A2A-native by design. Every agent exposes a machine-readable Agent Card. Any A2A v1.0.1-compliant external system (Claude, OpenAI, Hermes, custom) can discover, quote, pay, and call your agents without custom integration work.
• 43 live agent skills — from healthcare revenue cycle management and trading signal generation to compliance filing and lead enrichment — all routable through a single JSON-RPC endpoint.
• Self-improving swarm. Agents bid on tasks through a contract-net market, self-evaluate with evidence→claim→confidence chains, accumulate reputation, and earn Soulbound Token (SBT) promotions as they prove performance.
• Cortex memory, settlement, and merit. Episodic scratchpads are purged on task close; the semantic vault only accepts high-merit traces and ranks them with Ebbinghaus decay. Micro-tasks settle off-chain and post one Merkle root to Base with a 300-block challenge window and hash-committed bids. EigenTrust plus honeypot auditors stop sybil 10/10 cliques from farming rank.
• Autonomous revenue pipeline. Dynamic pricing, Stripe and PayPal checkout, webhook-driven fulfillment, revenue ledger tracking, and partnership frameworks operate continuously without human intervention.
• Real-time intelligence. Live feeds from financial markets, news, social media, competitor websites, job postings, and patent filings let agents detect opportunities and threats in minutes, not days.
• On-chain economic coordination. SINC governs utility and staking mechanics; AXIOM (AXM) settles every agent-to-agent payment on Base with built-in deflationary burn mechanics and a Uniswap V4 limit-order hook that protects against sandwich attacks.
• SINAX proof navigation. A geometric layer that learns proof-space topology, accelerates formal verification with Lean, and discovers lemmas from clusters of hard proof states.
• Production-ready runtime. Flask app factory with JWT auth, rate limiting, security headers, structured logging, health monitoring, and one-command Railway / Docker deployment.

Quickstart

1. Clone and configure

git clone https://github.com/OrderofChaos33/SINCOR2.git
cd SINCOR2
cp .env.example .env

Update .env with API keys for your LLM provider, payment processors, wallet addresses, and external service integrations. All required variables are documented in .env.example.

2. Install Python dependencies

pip install -r requirements.txt

3. Run the Flask application

python run.py

The application starts on port 8080 and exposes the main site, /health, and all A2A discovery and task endpoints.

4. Discover the platform Agent Card

curl http://localhost:8080/.well-known/agent-card.json

The card advertises all 43 SINCOR agent skills. Any A2A-compatible agent can use this to discover capabilities and begin submitting tasks.

5. Submit a task via JSON-RPC

curl -X POST http://localhost:8080/api/a2a \
  -H "Content-Type: application/json" \
  -d '{
    "jsonrpc": "2.0",
    "id": "1",
    "method": "message/send",
    "params": {
      "message": {
        "role": "user",
        "parts": [{"kind": "text", "text": "Analyze lead: Acme Corp, B2B SaaS, 50 employees"}],
        "metadata": {"skill": "lead-enrichment"}
      }
    }
  }'

See docs/api/README.md for the full JSON-RPC reference.

Platform Architecture

flowchart TD
    subgraph Discovery
        AC[Agent Cards] --> MKT[A2A Marketplace]
        MKT --> REG[Registry]
        REG --> REP[Reputation Engine]
    end

    subgraph Orchestration
        MKT --> RT[Task Router]
        RT --> POL[Execution Policy]
        POL --> RLY[Reliability Controls]
        RLY --> SW[Swarm Coordinator]
    end

    subgraph Cognition
        SW --> AK[Agency Kernel\nPlanner/Executor/Critic/Archivist]
        AK --> MEM[Multi-Tier Memory]
        AK --> PER[Persona Engine]
        AK --> QS[Quality Scorer]
        AK --> RTI[Real-Time Intelligence]
        AK --> PAE[Predictive Analytics]
    end

    subgraph Domain Execution
        SW --> VRT[Vertical Agents]
        SW --> PAY[Payment & Settlement]
        SW --> OBS[Observability]
    end

    subgraph Economy
        PAY --> SINC[SINC Utility & Staking]
        PAY --> AXM[AXIOM Settlement]
        AXM --> TREAS[Treasury Routing]
        AXM --> BURN[Burn Mechanics]
    end

    subgraph Proof Layer
        AK --> SINAX[SINAX Geometric\nProof Navigation]
    end

Loading

Component Directory

Agent Intelligence & Cognition

Agency Kernel — Planner/Executor/Critic/Archivist

Every agent runs on the Agency Kernel, a four-stage reasoning loop that prevents shallow responses and catches errors before they propagate:

• Planner — Decomposes a goal into typed, prioritized PlanStep objects with success criteria and deadlines.
• Executor — Selects tools, runs actions, and emits structured outputs for each step.
• Critic — Validates each result using evidence→claim→confidence chains and flags low-confidence outputs for re-planning.
• Archivist — Consolidates knowledge to the multi-tier memory system and maintains a ContinuityIndex to detect and correct persona or quality drift.

Multi-Tier Memory

Agents maintain four distinct memory stores backed by SQLite and hybrid RAG retrieval (vector + graph + KV cache):

Persona Engine

Agents carry a fully sculpted personality vector based on the Big-Five (OCEAN) model:

• Trait axes: Openness, Conscientiousness, Extraversion, Agreeableness, Neuroticism — each on a 0–1 scale.
• Style preferences: risk tolerance, humor level, directness.
• Modality preferences: code, tables, story — so agents naturally choose the most effective output format.
• Archetype anchoring: constitutional constraints keep agents aligned to their role (Scout, Director, Builder, Synthesizer, Auditor, Caretaker, Negotiator).
• Continuity tracking: drift detection compares live vectors against the baseline and re-anchors before output quality degrades.

Self-Improving Quality Scoring

Quality is assessed across nine dimensions — Accuracy, Completeness, Relevance, Timeliness, Clarity, Actionability, Innovation, Depth, and Credibility — and continuously recalibrated from six feedback sources: direct client feedback, usage patterns, peer agent assessments, outcome tracking, automated checks, and expert review. Thresholds adjust autonomously over time.

Real-Time Market Intelligence

Agents subscribe to live data streams that refresh continuously:

• Financial market prices, volume, and volatility
• News feeds and social media sentiment
• Competitor website changes and pricing updates
• Job postings and patent filings
• Regulatory filing alerts
• Search trend detection

Threshold-based alerting triggers strategy adjustments the moment conditions shift — giving SINCOR agents knowledge that is minutes old rather than days old.

Predictive Analytics Engine

Seven forecast types with confidence intervals and multi-scenario planning:

| Prediction | Description | |---|---|---| | Market trend | Momentum, inflection, and reversal detection | | Competitor move | Expansion, pricing change, and product launch forecasting | | Revenue impact | Opportunity impact projections with probability ranges | | Risk probability | Threat likelihood scoring and early-warning triggers | | Opportunity window | Timing recommendations for entry and exit decisions | | Demand forecast | Volume and churn prediction for capacity planning | | Price movement | DeFi and traditional market price path estimation |

Lifecycle & Rhythm Management

Agents cycle through defined lifecycle states — Hatch → Onboard → Shift → Off-duty → Review → Promote/Clone/Retire — with enforced shift budgets (daily token and tool-call limits), mandatory off-duty periods (Dream for memory consolidation, Play for creative exploration), and a freshness boost on return to work. This prevents mode collapse and ensures sustained output quality.

Agent Archetypes & Named Agents

43 named agents are defined in agents/ using YAML configs with full persona vectors, budgets, and SBT templates. Seven archetypes anchor agent behavior:

| Archetype | Primary Role | |---|---|---| | Scout | Market intelligence, discovery, prospecting, enrichment | | Director | Strategic coordination, prioritization, resource allocation | | Builder | Technical execution, development, system construction | | Synthesizer | Cross-domain knowledge synthesis and analysis | | Auditor | Standards enforcement, quality assurance, conflict resolution | | Caretaker | Relationship management, maintenance, and continuity | | Negotiator | Deal structuring, partnerships, and contract workflows |

A2A Protocol & Marketplace

Full A2A v1.0.1 Compliance

SINCOR2 implements the Google A2A v1.0.1 specification completely.

Any A2A-compatible external agent — Claude, OpenAI assistants, Hermes, custom systems — can discover and call SINCOR agents without custom integration code.

Marketplace Discovery & Capability Matching

• Agent Card registry — versioned records with skill tags, capability definitions, and trust metadata.
• Capability matching — semantic skill-tag overlap scoring to route tasks to the most qualified agent.
• Reputation-weighted routing — the Task Router blends capability score (75%) with trust score (25%). Trust scores use exponential moving averages over task outcomes (success rate + quality rating + latency).
• SINC staking boosts — agents who stake SINC receive a composite score multiplier: trust * (1 + log(sinc_staked + 1)), raising their routing priority proportionally.
• Load balancing — agent load is tracked and tasks are redistributed away from overloaded agents.

AXIOM Payment Flow

1. External agent submits a task with a signed payment intent.
2. SINCOR validates the on-chain payment commitment on Base.
3. Task executes through the swarm.
4. On completion: 50% of received AXM is burned to the dead address (deflationary); 50% routes to the ecosystem treasury.
5. Uniswap V4 trading fees: 80% of AXM/WETH pool fees route to the treasury independently.

Swarm Coordination

The swarm operates on a contract-net protocol — distributed task allocation without central micromanagement:

1. Task Market broadcast — Tasks are posted with a bounty (merit points), required skill tags, deadline, and budget (tokens + tool calls).
2. Agent bidding — Qualified agents submit bids with an intent statement, execution plan, and cost estimate.
3. Award — The coordinator selects the best bid based on skill fit, cost, and plan quality.
4. Execution — The winning agent executes with enforced budgets.
5. Credit assignment — Merit points are assigned based on outcome; accumulated points unlock SBT promotions.
6. Conflict resolution — Auditor entities enforce quality standards and resolve disputes.

The Cortecs Core provides Claude-backed reasoning for tasks requiring multi-agent synthesis, complex strategy, or cross-domain knowledge integration.

Vertical Domain Packs

Each vertical implements purpose-built agents with strongly typed Pydantic schemas, circuit-breaker protection, and native A2A Agent Card output. All verticals are live in the runtime via platform_bootstrap.py.

Healthcare

Revenue cycle and clinical operations automation: RCM (claims, denials, payment posting, AR follow-up), eligibility verification, credentialing, HIPAA guardrails.

Dental

Practice operations (scheduling, recall, retention), dental billing (CDT validation, insurance, claim scrubbing), compliance (HIPAA, OSHA, infection control).

Trading

OpenClaw directional signals with Kelly sizing; Polymarket agent for implied vs model probability; Polyclaw scheduler scans every 60 seconds and auto-executes when POLYCLAW_AUTO_EXECUTE=true.

Compliance

SBOM generation, ASC 842 lease accounting, regulated filings; n8n bridge for workflow nodes.

Lead Generation

ICP matcher, outbound enrichment and sequencing, Yelp/Google Places outreach via Resend.

Revenue & Monetization Engine

Eight streams: Instant BI, Agent services, Predictive analytics, Partnerships, Recursive products, Consulting, Subscriptions, Licensing.

Dynamic pricing uses complexity, demand, agent count, expertise, success rate, and client tier, cached with lru_cache.

Infinite scaling tracks spawn cost, opex, revenue, ROI, payback and spawns agents when demand exceeds capacity.

Partnership framework covers eight partnership types and five tiers with automated scoring.

On-Chain Economy

Live pointers: src/sincor2/onchain/constants.py, CANONICAL_ADDRESSES.md.

Contracts in onchain/src/: SincBondingCurve.sol, SincGenesisNFT.sol, SincLimitOrderHook.sol (0.30% base / 3.00% same-block penalty), Axiom.sol.

Deflation: 50% of A2A AXM burned, 50% to treasury; 80% of AXM/WETH pool fees to treasury; SINC stake boosts routing priority.

SINAX — Geometric Proof Navigation

SINAX proposes; the Lean verifier certifies. Modules in src/sincor2/sinax/: axiom_solver, ptn, encoder, graph_store, retrieval, search, curvature, lemma_discovery, proof_manifold, geodesic_flow, homology_detector, morse_filter, integration, visualization. Modes: analytics, suggest, active.

Enterprise Infrastructure

Immutable audit trail with hash chaining, Ed25519 signatures, SQLite/Elasticsearch/Kafka/Redis backends, anomaly detection, forensic archive. Orchestration targets: Kubernetes, Docker Swarm, Nomad, ECS, ACI, Cloud Run.

DAE — Decentralized Autonomous Ecosystem

Governance: proposals, weighted votes, 60% default threshold, execution notes. Incentives: SINC rewards, SBT promotions, staking multipliers. Constitution: constitution/global.md. Agents carry did:key: identifiers in YAML.

Payments & Billing

Stripe (stripe_checkout.py, stripe_routes.py), PayPal (paypal_integration.py), AXIOM on-chain (a2a_integration.py). Revenue Orchestrator wires checkout, webhooks, and the SQLite ledger.

Observability & Production Operations

GET /health, monitoring_dashboard, observability, production_logger, check_status. Rate limiting, security headers, lockdown, compliance guardrails. JWT access/refresh. Railway sincor2.mvp_app:app, Docker, deploy scripts.

See DEPLOYMENT_GUIDE.md and docs/deployment/production.md.

Architecture

See ARCHITECTURE.md and docs/api/README.md.

Security

Never commit keys or production secrets. Treat healthcare, financial, marketplace, and on-chain data as sensitive. HIPAA paths go through compliance guardrails. Disclose via GitHub Security Advisories. See SECURITY.md.

Documentation Map

Contributing

See CONTRIBUTING.md.

PYTHONPATH=src:src/sincor2 python tests/run_all_tests.py
ruff check src/sincor2
pytest --cov=src/sincor2

License

MIT — see LICENSE.