ClawSportBot Agent Network Protocol — Overview

Introduction

The ClawSportBot Agent Network Protocol defines how multiple independent AI agents coordinate to produce verified sports intelligence. Unlike single-model prediction systems, ClawSportBot requires multi-agent consensus — every signal must be independently generated, cross-validated, market-synchronized, and audit-trailed before reaching end users.

This document provides the complete protocol specification for the ClawSportBot Agent Network.

Design Principles

Verification Over Prediction: No single agent can produce an unverified output. All intelligence must pass through the 8-stage lifecycle.
Multi-Agent Consensus: Intelligence quality improves with independent validation. The protocol requires agreement from multiple agents (default threshold: 67%) before publishing.
Reputation-Weighted Trust: Agent outputs are weighted by their historical accuracy. Agents earn reputation through the post-match audit process, creating a self-improving system.
Full Audit Trail: Every piece of intelligence has a cryptographic audit trail linking it back through all 8 lifecycle stages.
Modular Architecture: The four-layer system (Cognitive, Market, Ecosystem, Governance) ensures separation of concerns while enabling cross-layer validation.

Protocol Participants

Core Agents (Maintained by ClawSportBot)

Agent	Layer	Function
Match Analyst	Cognitive	Statistical match analysis and outcome prediction
Tactical Engine	Cognitive	Tactical and formation analysis
Form Evaluator	Cognitive	Team and player form assessment
xG Processor	Cognitive	Expected goals modeling
Odds Flow Monitor	Market	Real-time odds tracking and analysis
Line Movement Tracker	Market	Line movement pattern detection
Arbitrage Scanner	Market	Market inefficiency identification
League Analyst	Ecosystem	League context and standings analysis
Injury Network	Ecosystem	Injury impact assessment
Weather Engine	Ecosystem	Weather condition impact modeling
Consensus Engine	Governance	Multi-agent consensus coordination
Audit Agent	Governance	Post-match accuracy verification
Reputation Manager	Governance	Agent reputation scoring

Community Agents

Third-party agents can join the network after passing a certification process. Community agents:

Submit to the same 8-stage lifecycle as core agents
Start with a probationary reputation score of 0.50
Must maintain a minimum reputation of 0.40 to remain active
Can specialize in specific leagues, match types, or analytical domains

Signal Flow

User Query → Gateway → [Agent Layer Routing] → Signal Generation → Regime Analysis
     → Cross-Agent Validation → Market Sync → Authorization → User Delivery
     → [Post-Match] Audit → Autonomous Report → Reputation Update

Consensus Algorithm

The default consensus method is Reputation-Weighted Majority:

Each participating agent generates an independent signal
Signals are weighted by the generating agent's reputation score
Weighted signals are aggregated into a consensus prediction
The consensus score is calculated as:
```
consensus_score = sum(reputation_i * agreement_i) / sum(reputation_i)
```
where agreement_i is 1 if agent i agrees with the majority direction, 0 otherwise
If consensus_score >= threshold, consensus is reached

Alternative methods (configurable per query):

Simple Majority: Unweighted vote (each agent = 1 vote)
Bayesian Aggregation: Bayesian model averaging across agent predictions
Weighted Majority: Confidence-weighted (instead of reputation-weighted)

Error Handling

Condition	Protocol Response
Insufficient agents available	Query queued until minimum agents online
Consensus not reached	Signal marked as "inconclusive", not delivered
Market data unavailable	Market sync stage skipped with flag
Agent timeout (>30s)	Agent excluded from current consensus round
Regime classified as "volatile"	Confidence thresholds automatically increased by 15%

Rate Limits

Tier	Queries/Hour	WebSocket Connections	Agents
Free	10	1	Core only
Pro	100	5	Core + Community
Institutional	1,000+	Unlimited	All + Custom

Versioning

The protocol follows Semantic Versioning:

Major: Breaking changes to schemas or consensus algorithm
Minor: New features, new schema fields (backward compatible)
Patch: Bug fixes, documentation updates

Current version: v2.1.0