swarm_predict

Orchestrate model agent swarms to produce consensus predictions via weighted, majority, or mean voting.

2|Updated Mar 17, 2026

Search Tags:#aggregation #consensus #swarm #prediction #ensemble #model_swarm

Ready to run

npx skills add https://github.com/jeremylongshore/oss-agent-lab --skill swarm-predict-jeremylongshore

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: swarm_predict
Source: https://github.com/jeremylongshore/oss-agent-lab/tree/main/agents/specialists/swarm_predict
Command: npx skills add https://github.com/jeremylongshore/oss-agent-lab --skill swarm-predict-jeremylongshore

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Coalesces multiple model predictions into a single, robust consensus to reduce bias and variance in predictions for dynamic targets.

Core Features & Use Cases

Ensemble prediction across diverse model types to improve accuracy.
Configurable swarm size, aggregation method, and consensus threshold for flexible deployments.
Stateless execution with deterministic results for the same target.

Quick Start

Provide a target and optional swarm size and method, then call the SwarmPredictSpecialist to receive a consensus result.

Frequently Asked Questions about swarm_predict

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I aggregate multiple model predictions into a single consensus result?▼

You aggregate multiple model predictions into a consensus by orchestrating a swarm of independent model agents, gathering their predictions, and combining results via weighted_vote, majority_vote, or mean aggregation methods.

How does ensemble swarm prediction reduce bias and variance for dynamic targets?▼

Ensemble swarm prediction reduces bias and variance by coalescing diverse model types into a single robust consensus, evaluating agreement against a configurable threshold to improve overall accuracy for dynamic targets.

Can I configure the swarm size and aggregation method for consensus predictions?▼

Yes, you can configure the swarm size, aggregation method, and consensus threshold for flexible deployments. The execution is stateless, returning deterministic results for the same target input.

What is the best way to get a confidence score from an ensemble prediction swarm?▼

The best way to get a confidence score is to call the prediction swarm with a target and method. It returns a structured response containing the consensus result, confidence level, and a swarm_id.

Does the consensus prediction swarm support both numeric and categorical targets?▼

Yes, the consensus prediction swarm supports both numeric and categorical targets, returning a structured response with the target, predictions, consensus, confidence, and swarm_id across Python API, CLI, and REST API integrations.

When should I not use a consensus threshold for model aggregation?▼

You should evaluate your consensus threshold carefully when working with highly diverse independent model agents, as a strict threshold may reject valid predictions if the swarm lacks sufficient agreement on the target.