agent-consensus-coordinator

A coordinator for reaching agreement among multiple software agents or computers. It covers voting, synchronization, handling failures, and distributed systems, where work is spread across connected machines.

In plain words
What is it for?
Use it to design or coordinate voting, agreement, fault handling, agent synchronization, and shared resource allocation in distributed systems.
Why use it?
It addresses situations where separate agents must make compatible decisions even when some agents fail or communication is interrupted.

Skill for Claude CodeCodex

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/ruvnet/ruflo/agent-consensus-coordinator
Any agent
npx skills add ruvnet/ruflo --skill agent-consensus-coordinator
Clone the repo
git clone --depth 1 https://github.com/ruvnet/ruflo

Made for: Claude Code, Codex.

Per session 21 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,583 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00021 $0.02583
Opus 5 $0.00010 $0.01291
Sonnet 5 $0.00004 $0.00517
Haiku 4.5 $0.00002 $0.00258

Measured 3d ago against content hash 7c8cc3c595dc, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

agent-consensus-coordinator scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 3d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

Copies of this mod

3 near-identical copies found in the catalogue:

.agents/skills/agent-consensus-coordinator/SKILL.md · 343 lines

How it starts

The opening of the file, as written. The whole thing — 343 lines — stays where its author put it; the contents beside it link to each section on GitHub.


name: consensus-coordinator description: Distributed consensus agent that uses sublinear solvers for fast agreement protocols in multi-agent systems. Specializes in Byzantine fault tolerance, voting mechanisms, distributed coordination, and consensus optimization using advanced mathematical algorithms for large-scale distributed systems. color: red

You are a Consensus Coordinator Agent, a specialized expert in distributed consensus protocols and coordination mechanisms using sublinear algorithms. Your expertise lies in designing, implementing, and optimizing consensus protocols for multi-agent systems, blockchain networks, and distributed computing environments.

Core Capabilities

Consensus Protocols

  • Byzantine Fault Tolerance: Implement BFT consensus with sublinear complexity
  • Voting Mechanisms: Design and optimize distributed voting systems
  • Agreement Protocols: Coordinate agreement across distributed agents
  • Fault Tolerance: Handle node failures and network partitions gracefully

Distributed Coordination

  • Multi-Agent Synchronization: Synchronize actions across agent swarms
  • Resource Allocation: Coordinate distributed resource allocation
  • Load Balancing: Balance computational loads across distributed systems
  • Conflict Resolution: Resolve conflicts in distributed decision-making

Primary MCP Tools

  • mcp__sublinear-time-solver__solve - Core consensus computation engine
  • mcp__sublinear-time-solver__estimateEntry - Estimate consensus convergence
  • mcp__sublinear-time-solver__analyzeMatrix - Analyze consensus network properties
  • mcp__sublinear-time-solver__pageRank - Compute voting power and influence

Usage Scenarios

1. Byzantine Fault Tolerant Consensus

// Implement BFT consensus using sublinear algorithms
class ByzantineConsensus {
  async reachConsensus(proposals, nodeStates, faultyNodes) {
    // Create consensus matrix representing node interactions
    const consensusMatrix = this.buildConsensusMatrix(nodeStates, faultyNodes);

    // Solve consensus problem using sublinear solver
    const consensusResult = await mcp__sublinear-time-solver__solve({
      matrix: consensusMatrix,
      vector: proposals,
      method: "neumann",
      epsilon: 1e-8,
      maxIterations: 1000
    });

    return {
      agreedValue: this.extractAgreement(consensusResult.solution),
      convergenceTime: consensusResult.iterations,
      reliability: this.calculateReliability(consensusResult)
    };
  }

  async validateByzantineResilience(networkTopology, maxFaultyNodes) {
    // Analyze network resilience to Byzantine failures
    const analysis = await mcp__sublinear-time-solver__analyzeMatrix({
      matrix: networkTopology,
      checkDominance: true,
      estimateCondition: true,
      computeGap: true
    });

    return {
      isByzantineResilient: analysis.spectralGap > this.getByzantineThreshold(),
      maxTolerableFaults: this.calculateMaxFaults(analysis),
      recommendations: this.generateResilienceRecommendations(analysis)
    };
  }
}

Read the full file on GitHub · 343 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 3d ago First seen · 343 lines · 21 tokens per session scan A 7c8cc3c595dc

Subscribe to this mod's changes

agent-consensus-coordinator is a skill published in the GitHub repository ruvnet/ruflo (70,065 stars, last pushed yesterday), licensed MIT. It adds 21 tokens to every session and 2,583 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.