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Byzantine consensus voting for multi-agent decision making. Implements voting protocols, conflict resolution, and agreement algorithms for reaching consensus among multiple agents.
version
1.1.0
model
sonnet
invoked_by
both
user_invocable
true
tools
["Read","Write","Edit","Bash","Glob","Grep"]
best_practices
["Require minimum quorum for decisions","Weight votes by agent expertise","Document dissenting opinions","Escalate unresolved conflicts"]
error_handling
graceful
streaming
supported
verified
true
lastVerifiedAt
"2026-02-22T00:00:00.000Z"
source
builtin
trust_score
100
provenance_sha
703e59a226d61676
Consensus Voting Skill
Consensus Voting Skill - Implements voting protocols and conflict resolution algorithms for reaching consensus among multiple agents with potentially conflicting recommendations.
- Collecting votes from multiple agents
- Weighted voting based on expertise
- Conflict detection and resolution
- Quorum verification
- Decision documentation
Step 1: Define Voting Parameters
Set up the voting session:
voting_session:topic:'Which database to use for the new service'options:-PostgreSQL-MongoDB-DynamoDBquorum:3# Minimum votes requiredthreshold:0.6# 60% agreement neededweights:database-architect:2.0# Expert gets 2x weightsecurity-architect:1.0devops:1.5
If domain expert has strong opinion (>0.8 confidence), defer to expert
Strategy 2: Discussion Round
Ask dissenting agents to respond to majority arguments
Re-vote after discussion
Strategy 3: Escalation
Present options to user with pros/cons from each agent
Let user make final decision
Step 5: Document Decision
Record the final decision:
## Decision Record### Topic
Which database to use for the new service
### Decision
PostgreSQL
### Voting Summary- PostgreSQL: 57.8% (2 votes)
- DynamoDB: 23.3% (1 vote)
- Consensus: NOT REACHED (below 60% threshold)
### Resolution Method
Expert override - database-architect (domain expert)
had 0.9 confidence in PostgreSQL
### Dissenting Opinion
DevOps preferred DynamoDB for operational simplicity.
Mitigation: Will use managed PostgreSQL (RDS) to
reduce operational burden.
### Decision Date
2026-01-23
</execution_process>
<best_practices>
Quorum Required: Don't decide without minimum participation
Weight by Expertise: Domain experts get more influence
Document Dissent: Record minority opinions for future reference
Clear Thresholds: Define what constitutes consensus upfront
Escalation Path: Have a process for unresolved conflicts
</best_practices>
The architect wants microservices but the developer prefers monolith.
Resolve this conflict.
Prevents premature closure of council or multi-agent tasks by requiring 2+ agents to independently confirm task completion before the session closes.
Problem
A single agent signaling "done" can produce incomplete results -- the agent may have finished its own subtask but the overall task is not complete. The dual-completion gate requires consensus on completion itself.
Require min_completions (default: 2) signals within a window_seconds time window (default: 60s)
If only 1 agent signals completion, send a "verification nudge" to remaining agents after nudge_after_seconds (default: 30s)
After fallback_timeout (default: 120s) with only 1 completion, accept single-agent completion with a warning: "single_agent_completion" flag
Configuration
completion_gate:min_completions:2# minimum agents that must signal donewindow_seconds:60# time window for completion consensusnudge_after_seconds:30# send nudge to remaining agents after first completionfallback_timeout:120# accept single completion after this timeout (with warning)
Pseudocode
completions = []
on_agent_complete(agent_id):
completions.push({ agent_id, timestamp: now() })
if completions.length >= min_completions:
window_start = completions[0].timestamp
window_end = completions[-1].timestamp
if (window_end - window_start) <= window_seconds:
return CLOSE_SESSION(status: "consensus_complete")
if completions.length == 1:
schedule_nudge(nudge_after_seconds)
schedule_fallback(fallback_timeout)
on_nudge_timeout():
send_to_remaining_agents("A team member has signaled completion. Please confirm if the task is done.")
on_fallback_timeout():
if completions.length < min_completions:
return CLOSE_SESSION(status: "single_agent_complete", warning: "single_agent_completion")
Integration with LLM Council
The dual-completion gate is invoked by the llm-council skill before closing a council session:
After Stage 3 synthesis, each model is asked: "Is this synthesis complete and accurate?"
Models respond with "complete" or "needs_revision"
The gate requires min_completions "complete" signals before closing
If gate fails (insufficient completions), chairman reviews and decides
Voting Protocols Table Update
Protocol
Use Case
Threshold
Quorum
Simple Majority
Routine decisions
>50%
50%
Supermajority
Significant changes
>=66%
75%
Unanimous
Critical/irreversible decisions
100%
100%
Weighted
Specialized expertise required
Variable
66%
Ranked Choice
Multiple alternatives
Runoff
75%
Dual Completion
Council task closure
2 agents confirm
100%
Rules
Always require quorum before deciding
Weight votes by domain expertise
Document dissenting opinions for future reference
Require dual-agent completion consensus before closing council sessions
Related Workflow
This skill has a corresponding workflow for complex multi-agent scenarios:
When to use workflow: For critical multi-agent decisions requiring Byzantine fault-tolerant consensus with Queen/Worker topology (architectural decisions, security reviews, technology selection)
When to use skill directly: For simple voting scenarios or when integrating consensus into other workflows
Workflow Integration
This skill enables decision-making in multi-agent orchestration:
swarm-coordination skill for parallel agent spawning before voting
Enterprise workflows use consensus for design reviews
Security reviews in .claude/workflows/enterprise/ require security-architect consensus
Iron Laws
NEVER accept a decision without meeting minimum quorum — decisions made without quorum are illegitimate; if quorum is not met, postpone the decision or escalate to human intervention.
ALWAYS weight votes by domain expertise — equal weights give a generalist developer the same influence as a domain expert; weight by expertise relevance to the decision domain.
NEVER discard dissenting opinions — minority perspectives contain the most important signal about edge cases and risks; document all rationales, including the losing side.
ALWAYS require re-vote with deliberation before escalating — a split vote without deliberation wastes the consensus mechanism; agents must share reasoning and vote again before escalating to human.
NEVER allow abstentions in critical decisions — abstentions on high-stakes decisions mean agents are avoiding responsibility; all participants must vote on CRITICAL/UNANIMOUS-threshold decisions.
Anti-Patterns
Anti-Pattern
Why It Fails
Correct Approach
No quorum requirement
Tiny group decides for all; illegitimate consensus
Set minimum participation threshold per decision type
Equal weights for all agents
Ignores domain expertise; reduces signal quality
Weight by domain expertise relevance (1.0–2.0 range)
Discarding dissenting rationales
Loses edge case awareness and risk signals
Document all votes and rationales, majority and minority
Immediate escalation on split vote
Skips deliberation that could resolve disagreement
Require deliberation + re-vote before human escalation
Allowing abstentions on critical decisions
Agents avoid accountability on hard decisions
Require participation from all eligible voters on CRITICAL decisions
Memory Protocol (MANDATORY)
Before starting:
cat .claude/context/memory/learnings.md
After completing:
New pattern -> .claude/context/memory/learnings.md
Issue found -> .claude/context/memory/issues.md
Decision made -> .claude/context/memory/decisions.md
ASSUME INTERRUPTION: Your context may reset. If it's not in memory, it didn't happen.
