consensus-voting
- Repo stars 39
- Author updated Live
- Author repo awesome-omni-skill
- Domain
- AI
- Compatible agents
-
- Claude Code
- Cursor
- Cline
- Codex
- Windsurf
- Gemini CLI
- +20
- Trust score
- 92 / 100 · audit passed
- Author / version / license
- @diegosouzapw · v1.0 · no license declared
- Token usage
- Lean
- Setup complexity
- Guided setup
- External API key
- Not required
- Operating systems
- Unspecified (assume cross-platform)
- Runtime requirements
- No special requirements
- Permissions
-
- Read-only
- Shell exec
- Write / modify
- Network behavior
- Local-only
- Install commands
- 26 variants
Profile is derived at build time from SKILL.md and install vectors. Subject to drift from author intent.
Heads up: 未限定 allowed-tools，默认拥有全部工具权限。
---
name: consensus-voting
description: Byzantine consensus voting for multi-agent decision making. Implements voting protocols, conflic…
category: ai
runtime: no special runtime
---
# consensus-voting output preview
## PART A: Task fit
- Use case: Byzantine consensus voting for multi-agent decision making. Implements voting protocols, conflict resolution, and agreement algorithms for reaching consensus among multiple agents..
- Inputs: target material, constraints, expected output, and acceptance criteria.
- Evidence boundary: follow “Step 1: Define Voting Parameters / Step 2: Collect Votes / Vote Collection” and do not present inference as author intent.
## PART B: Execution result
- **01** The card summarizes the use case; runtime output centers on “Byzantine consensus voting for multi-agent decision making. Implements voting protocols, conflict resolution, and agreement algorithms for reaching consensus among multiple agents.”.
- **02** When the source has headings, the agent prioritizes “Step 1: Define Voting Parameters / Step 2: Collect Votes / Vote Collection” so the result follows the author’s structure.
- **03** Typical output includes task judgment, concrete steps, required commands or file edits, validation, and follow-up options.
- **04** Risk context follows the fingerprint: read files, run shell commands, write/modify files; mostly runs locally; usually needs no extra API key.
## Running Rules
- read files, run shell commands, write/modify files; mostly runs locally; usually needs no extra API key.
- Validate with a small sample before expanding scope.
- Return the result, validation criteria, and next iteration options. Choose the trigger
The source does not require a stable slash command. After installation, invoke the skill by name and describe the task.
Provide inputs and boundaries
Name target files or source material, expected output, forbidden changes, and whether network or shell access is allowed. Permission fingerprint: read files, run shell commands, write/modify files.
Validate with a small run
Start with a small task and check whether the result follows “Step 1: Define Voting Parameters / Step 2: Collect Votes / Vote Collection”. Inspect diffs, logs, previews, or tests before expanding scope.
Review before delivery
Confirm the final output includes a concrete result, evidence, and next action. If it stays generic, tighten inputs, boundaries, and acceptance criteria.
---
name: consensus-voting
description: Byzantine consensus voting for multi-agent decision making. Implements voting protocols, conflic…
category: ai
source: diegosouzapw/awesome-omni-skill
---
# consensus-voting
## When to use
- Byzantine consensus voting for multi-agent decision making. Implements voting protocols, conflict resolution, and agre…
- Use it when the task has clear inputs, repeatable steps, and validation criteria.
## What to provide
- Target material, scope, expected result, and forbidden changes.
- Whether network, commands, file writes, or external services are allowed.
## Execution rules
- Organize steps around “Step 1: Define Voting Parameters / Step 2: Collect Votes / Vote Collection” and keep inference separate from source facts.
- read files, run shell commands, write/modify files; mostly runs locally; usually needs no extra API key.
- Validate with a small sample before expanding the task.
## Output requirements
- Return the deliverable, key evidence, validation method, and next action.
- Mark missing information as unknown; do not invent commands, platforms, or dependencies. Evidence boundary and execution chain
The author source anchors workflow facts; repository files anchor sources and commands; Fluxly only adds fit, limitations, and quality judgment.
skill "consensus-voting" {
input -> user goal + target files + boundaries + acceptance criteria
context -> Step 1: Define Voting Parameters / Step 2: Collect Votes / Vote Collection
rules -> SKILL.md triggers / order / output contract
runtime -> no special runtime | read files, run shell commands, write/modify files | mostly runs locally
guardrails -> usually needs no extra API key + small-sample validation + diff/log review
output -> copyable result + checklist + next iteration
}Consensus Voting Skill
Step 1: Define Voting Parameters
Set up the voting session:
voting_session:
topic: 'Which database to use for the new service'
options:
- PostgreSQL
- MongoDB
- DynamoDB
quorum: 3 # Minimum votes required
threshold: 0.6 # 60% agreement needed
weights:
database-architect: 2.0 # Expert gets 2x weight
security-architect: 1.0
devops: 1.5Step 2: Collect Votes
Gather agent recommendations:
## Vote Collection
### database-architect (weight: 2.0)
- Vote: PostgreSQL
- Rationale: Strong ACID guarantees, mature ecosystem
- Confidence: 0.9
### security-architect (weight: 1.0)
- Vote: PostgreSQL
- Rationale: Better encryption at rest, audit logging
- Confidence: 0.8
### devops (weight: 1.5)
- Vote: DynamoDB
- Rationale: Managed service, auto-scaling
- Confidence: 0.7Step 3: Calculate Consensus
Apply weighted voting:
PostgreSQL: (2.0 * 0.9) + (1.0 * 0.8) = 2.6
DynamoDB: (1.5 * 0.7) = 1.05
MongoDB: 0
Total weight: 4.5
PostgreSQL: 2.6 / 4.5 = 57.8%
DynamoDB: 1.05 / 4.5 = 23.3%
Threshold: 60% → No clear consensusStep 4: Resolve Conflicts
When no consensus is reached:
Strategy 1: Expert Override
- 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- 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
The architect wants microservices but the developer prefers monolith.
Resolve this conflict.Voting Process:
## Voting: Architecture Style
### Votes
- architect: Microservices (weight 1.5, confidence 0.8)
- developer: Monolith (weight 1.0, confidence 0.9)
- devops: Microservices (weight 1.0, confidence 0.6)
### Calculation
Microservices: (1.5 _ 0.8) + (1.0 _ 0.6) = 1.8
Monolith: (1.0 \* 0.9) = 0.9
Microservices: 66.7% → CONSENSUS REACHED
### Decision
Microservices, with modular monolith as migration path
### Dissent Mitigation
Start with modular monolith, extract services incrementally
to address developer's maintainability concerns.Rules
- Always require quorum before deciding
- Weight votes by domain expertise
- Document dissenting opinions for future reference
Related Workflow
This skill has a corresponding workflow for complex multi-agent scenarios:
- Workflow:
.claude/workflows/consensus-voting-skill-workflow.md - 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:
Router Decision: .claude/workflows/core/router-decision.md
- Router spawns multiple reviewers, then uses consensus to resolve conflicts
- Planning Orchestration Matrix triggers consensus voting for review phases
Artifact Lifecycle: .claude/workflows/core/skill-lifecycle.md
- Consensus voting determines artifact deprecation decisions
- Multiple maintainers vote on breaking changes
Related Workflows:
swarm-coordinationskill for parallel agent spawning before voting- Enterprise workflows use consensus for design reviews
- Security reviews in
.claude/workflows/enterprise/require security-architect consensus
Memory Protocol (MANDATORY)
Before starting:
cat .claude/context/memory/learnings.mdAfter 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.
Decide Fit First
Design Intent
How To Use It
Boundaries And Review