name: analysis-experiments
description: "Collect Mesa experiment data, run scenario sweeps, and use
experimental actions, states, signals, and meta-agent analysis helpers."
disable-model-invocation: true
metadata:
disco-role: operating
license: Apache 2.0
Analysis Experiments
Use this sub-skill when a Mesa task is about experiment outputs, scenario orchestration, or experimental analysis helpers rather than basic model structure or visualization.
Use for
DataCollector reporters, model / agent / agent-type DataFrames, and manual tables.
- Experimental
mesa.experimental.data_collection datasets, registries, and recorders.
- Experimental
Scenario, RunConfiguration, run_scenarios, stores, statuses, and failure diagnostics.
- Experimental timed
Action lifecycles, continuous states, thresholds, reactive signals, and batching.
- Experimental
MetaAgent grouping utilities for higher-order agent analysis.
Start here
- API reference for signatures, import paths, return shapes, and stability notes.
- Workflows for copyable collection, recorder, scenario, signal/state/action, and meta-agent recipes.
- Troubleshooting for reporter validation, recorder setup, scenario failure origins, pickling, and experimental API pitfalls.
- DataCollector smoke script for a safe installed-package check that emits JSON summaries.
- Scenario smoke script for a safe installed-package check of
Scenario, RunConfiguration, run_scenarios, and failure recording.
Route elsewhere
- Core
Model, Agent, AgentSet, activation, RNG, and event scheduling basics: model-core
- Spatial placement, movement, grids, networks, cells, or continuous-space geometry: spaces
- Solara dashboards, browser visualization, plotting widgets, charts, or rendering: visualization
All APIs under mesa.experimental are experimental and may change between Mesa releases. Treat this sub-skill as the self-contained operating reference; no external repository files are required at runtime.