| name | swarm_predict |
| display_name | Swarm Prediction Specialist |
| description | Ensemble predictions via swarm intelligence with multi-model voting and consensus |
| version | 0.1.0 |
| source_repo | 666ghj/MiroFish |
| license | MIT |
| tier | core |
| capabilities | ["predict","ensemble","swarm_intelligence","consensus"] |
| allowed_tools | ["create_prediction_swarm","aggregate_predictions","evaluate_consensus"] |
| output_formats | ["python_api","cli","mcp_server","agent_skill","rest_api"] |
Swarm Prediction Specialist
Overview
swarm_predict wraps the swarm intelligence prediction patterns from
666ghj/MiroFish. Rather than relying
on a single model, it spins up a configurable swarm of independent model
agents, collects their individual predictions, and resolves a consensus
through weighted aggregation and agreement scoring.
The specialist is fully stateless — each request spawns a fresh swarm and
returns a self-contained result dict. It supports numeric and categorical
prediction targets and exposes three aggregation strategies: weighted vote,
majority vote, and simple mean.
Capabilities
- predict: Route any prediction target through the swarm pipeline and
receive a consensus value with confidence score.
- ensemble: Combine outputs from N independent model agents (default 5)
to reduce variance and single-model bias.
- swarm_intelligence: Each agent operates independently before results
are merged, mirroring biological swarm behaviour.
- consensus: Agreement ratio and blended confidence score surface when
models agree strongly enough to act on the prediction.
Tools
| Tool | Description | Side Effects |
|---|
create_prediction_swarm | Initialise N model agents for a given target | None |
aggregate_predictions | Merge individual predictions via weighted/majority/mean vote | None |
evaluate_consensus | Score agreement ratio and emit a recommendation | None |
Parameters
Request-level (intent.parameters)
| Key | Type | Default | Description |
|---|
target | str | (query.user_input) | Prediction target; falls back to the raw user query |
num_models | int | 5 | Swarm size |
method | str |
