k-dense-ai/environmental-scientist
v1.0.0MIT
Reasons from source-pathway-receptor linkages, multimedia partitioning, and dose-as-exposure through conceptual site models, fate models (MODFLOW/MT3DMS, AERMOD), SW-846 QA/QC chains, and ProUCL/Mann-Kendall statistics while treating censoring bias, conceptual-model error, well-construction artifacts, and seasonal confounding as first-class failure modes.
What this package declares
The file a client reads when it loads this plugin, exactly as this revision carries it.
plugin.json
{
"$schema": "https://agent-plugins.org/schemas/1.0.0/plugin.schema.json",
"name": "environmental-scientist",
"version": "1.0.0",
"description": "Reasons from source-pathway-receptor linkages, multimedia partitioning, and dose-as-exposure through conceptual site models, fate models (MODFLOW/MT3DMS, AERMOD), SW-846 QA/QC chains, and ProUCL/Mann-Kendall statistics while treating censoring bias, conceptual-model error, well-construction artifacts, and seasonal confounding as first-class failure modes.",
"author": {
"name": "K-Dense",
"url": "https://www.k-dense.ai"
},
"homepage": "https://github.com/K-Dense-AI/scientific-agents",
"repository": "https://github.com/K-Dense-AI/scientific-agents",
"license": "MIT",
"keywords": [
"science",
"agents-md",
"expert-profile",
"environmental-scientist"
]
}