skills/minerals-gov-monitor/SKILL.md
Monitor government and regulator releases relevant to critical minerals and materials via domain-targeted web discovery with policy tagging
npx skillsauth add lamm-mit/scienceclaw minerals-gov-monitorInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Monitor policy and release signals from government and regulator domains (US, EU, UK, Canada, Australia, OECD by default).
# Default government domain set
python3 {baseDir}/scripts/gov_monitor.py --commodity lithium --commodity rare_earth
# Custom domain allowlist
python3 {baseDir}/scripts/gov_monitor.py \
--domains usgs.gov,energy.gov,europa.eu,gov.uk \
--country china --country united states --format json
| Parameter | Description | Default |
|-----------|-------------|---------|
| --domains | Comma-separated domain allowlist | built-in gov list |
| --commodity | Commodity term (repeatable) | - |
| --country | Country term (repeatable) | - |
| --max-results | Max records returned | 25 |
| --format | summary, detailed, json | summary |
Each record includes:
url, source, published_at, title, summary, commodity_tags, country_tags, policy_signal, confidence, retrieved_at, source_type, monitor_domain.
site:domain ...) for targeted discovery.minerals-web-ingest to fetch and store full content for downstream indexing.tools
Onboard and manage Paperclip AI for research-paper knowledge and agent orchestration
development
Perform AI-powered web searches with real-time information using Perplexity models via LiteLLM and OpenRouter. This skill should be used when conducting web searches for current information, finding recent scientific literature, getting grounded answers with source citations, or accessing information beyond the model knowledge cutoff. Provides access to multiple Perplexity models including Sonar Pro, Sonar Pro Search (advanced agentic search), and Sonar Reasoning Pro through a single OpenRouter API key.
testing
Generate a structured scientific PDF report from a JSON description. Accepts a JSON file specifying title, authors, abstract, sections (headings, text, tables, figures), and inline data panels (heatmap, bar, scatter, line). Produces a publication-style A4 PDF using reportlab with no LaTeX dependency. All figures are either loaded from PNG paths or generated on-the-fly from inline data.
development
Execute arbitrary Python code and return stdout. NumPy, pandas, scipy, matplotlib, and other scientific libraries are available.