consensus-mechanisms
Multi-protocol consensus for agent swarms supporting Raft leader election, Byzantine fault tolerance, Gossip state propagation, and CRDT conflict-free merging.
Best use case
consensus-mechanisms is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Multi-protocol consensus for agent swarms supporting Raft leader election, Byzantine fault tolerance, Gossip state propagation, and CRDT conflict-free merging.
Teams using consensus-mechanisms should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/consensus-mechanisms/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How consensus-mechanisms Compares
| Feature / Agent | consensus-mechanisms | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Multi-protocol consensus for agent swarms supporting Raft leader election, Byzantine fault tolerance, Gossip state propagation, and CRDT conflict-free merging.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# Consensus Mechanisms ## Overview Implement distributed consensus among agent swarms. Select the appropriate protocol based on fault tolerance requirements, swarm size, and communication topology. ## When to Use - Multiple agents have produced independent solutions needing reconciliation - Byzantine fault tolerance is required (untrusted or unreliable agents) - State synchronization across distributed agent swarms - Conflict-free data merging in concurrent operations ## Protocols | Protocol | Use Case | Fault Tolerance | Complexity | |----------|----------|-----------------|------------| | Raft | Leader-based consensus, ordered log | Crash faults (f < n/2) | Medium | | Byzantine | Untrusted agents, adversarial conditions | Byzantine faults (f < n/3) | High | | Gossip | Eventual consistency, state propagation | Partition tolerant | Low | | CRDT | Conflict-free replicated data types | Always convergent | Low | ## Weighted Voting - Queen agents: 3x weight multiplier - Worker agents: 1x weight - Configurable consensus threshold (majority, supermajority, unanimous) ## Agents Used - `agents/swarm-coordinator/` - Protocol orchestration - `agents/strategic-queen/` - Weighted voting leadership ## Tool Use Invoke via babysitter process: `methodologies/ruflo/ruflo-swarm-coordination`
Related Skills
consensus-protocol-library
Reference implementations and specifications of consensus protocols
process-builder
Scaffold new babysitter process definitions following SDK patterns, proper structure, and best practices. Guides the 3-phase workflow from research to implementation.
babysitter
Orchestrate via @babysitter. Use this skill when asked to babysit a run, orchestrate a process or whenever it is called explicitly. (babysit, babysitter, orchestrate, orchestrate a run, workflow, etc.)
yolo
Run Babysitter autonomously with minimal manual interruption.
user-install
Install the user-level Babysitter Codex setup.
team-install
Install the team-pinned Babysitter Codex workspace setup.
retrospect
Summarize or retrospect on a completed Babysitter run.
resume
Resume an existing Babysitter run from Codex.
project-install
Install the Babysitter Codex workspace integration into the current project.
plan
Plan a Babysitter workflow without executing the run.
observe
Observe, inspect, or monitor a Babysitter run.
model
Inspect or change Babysitter model-routing policy by phase.