air-quality-scientist
v1.0.0Reasons from source emissions through transformation, transport, and dose using SMOKE/MOVES inventories, WRF-driven CTMs like CMAQ and CAMx, PMF/ME-2 apportionment, and concentration-response functions, while treating rotational PMF ambiguity, AOD-to-PM bias in humid regions, uncalibrated low-cost sensors, and untreated wildfire exceptional events as first-class failure modes.
By K-Dense-AILicense: MIT199 GitHub starsUpdated 5 days ago
Directory evidence
- Runtimes
- Claude Code and Agent Plugins
- Parsed components
- 1 skill or MCP entry
- Source updated
- Oct 2, 2026
- Manifest status
- Canonical path parsed
The directory validates manifest shape and source location. It does not execute the plugin or provide a security endorsement. Review the indexing methodology →
Install air-quality-scientist for Claude Code
claude plugin marketplace add IchenDEV/agent-plugin-mkt
claude plugin marketplace update agent-plugin-marketplace
claude plugin install air-quality-scientist@agent-plugin-marketplacePaste and run these commands in a terminal with Claude Code. They add and refresh the PluginsMP catalog, then install this plugin.
The installer fetches third-party code from the source repository shown on this page. This directory validates manifest structure and source location, but does not perform a security audit; review the manifest, components, and source before installing.
Get the source manually
git clone https://github.com/K-Dense-AI/scientific-agentsClone the source repository, then follow its setup instructions to add the plugin to a compatible client. The plugin root is scientific-agents/air-quality-scientist/.
Plugin files
├── .claude-plugin/plugin.json├── plugin.json└── skills/air-quality-scientist/SKILL.md
Included Skills1
Think and work like an expert Air Quality Scientist. Use when a task calls for Air Quality Scientist judgment. Reasons from source emissions through transformation, transport, and dose using SMOKE/MOVES inventories, WRF-driven CTMs like CMAQ and CAMx, PMF/ME-2 apportionment, and concentration-response functions, while treating rotational PMF ambiguity, AOD-to-PM bias in humid regions, uncalibrated low-cost sensors, and untreated wildfire exceptional events as first-class failure modes.
Plugin manifests2
{
"name": "air-quality-scientist",
"version": "1.0.0",
"description": "Reasons from source emissions through transformation, transport, and dose using SMOKE/MOVES inventories, WRF-driven CTMs like CMAQ and CAMx, PMF/ME-2 apportionment, and concentration-response functions, while treating rotational PMF ambiguity, AOD-to-PM bias in humid regions, uncalibrated low-cost sensors, and untreated wildfire exceptional events as first-class failure modes.",
"author": {
"name": "K-Dense-AI",
"url": "https://github.com/K-Dense-AI"
},
"homepage": "https://github.com/K-Dense-AI/scientific-agents",
"keywords": [
"science",
"agents-md",
"expert-profile",
"air-quality-scientist"
]
}{
"$schema": "https://agent-plugins.org/schemas/1.0.0/plugin.schema.json",
"name": "air-quality-scientist",
"version": "1.0.0",
"description": "Reasons from source emissions through transformation, transport, and dose using SMOKE/MOVES inventories, WRF-driven CTMs like CMAQ and CAMx, PMF/ME-2 apportionment, and concentration-response functions, while treating rotational PMF ambiguity, AOD-to-PM bias in humid regions, uncalibrated low-cost sensors, and untreated wildfire exceptional events 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",
"air-quality-scientist"
]
}For maintainers
If you maintain this plugin, link to this source-backed listing from your README so users can review its manifest and indexed components.
[air-quality-scientist on Agent Plugins Marketplace](https://pluginsmp.com/plugins/air-quality-scientist)