Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add beita6969/ScienceClaw --skill environmental-sciencegit clone --depth 1 https://github.com/beita6969/ScienceClawWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/beita6969/scienceclaw/environmental-science)<a href="https://agentmods.dev/skills/beita6969/scienceclaw/environmental-science"><img src="https://agentmods.dev/badge/skills/beita6969/scienceclaw/environmental-science/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/beita6969/scienceclaw/environmental-science"><img src="https://agentmods.dev/badge/skills/beita6969/scienceclaw/environmental-science.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00044 | $0.00697 |
| Opus 5 | $0.00022 | $0.00349 |
| Sonnet 5 | $0.00009 | $0.00139 |
| Haiku 4.5 | $0.00004 | $0.00070 |
Grade A, and why
environmental-science scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 8d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 53 lines — stays where its author put it; the contents beside it link to each section on GitHub.
When to Trigger
Activate this skill when the user mentions:
- Climate data, temperature anomalies, CO2 levels, greenhouse gases
- Air/water quality, pollutant concentrations, EPA standards
- Ecological modeling, species distribution, biodiversity indices
- Carbon footprint, life cycle assessment (LCA), emissions inventory
- Remote sensing, satellite imagery for environmental monitoring
- Deforestation, habitat loss, conservation planning
- Ocean acidification, sea level rise, ice sheet dynamics
Step-by-Step Methodology
- Define the environmental question - Specify the spatial scale (local, regional, global), temporal range, and environmental domain (atmosphere, hydrosphere, lithosphere, biosphere).
- Data acquisition - Identify appropriate datasets: NOAA/NASA for climate, EPA for pollution, GBIF for biodiversity, Copernicus for satellite data. Check data quality, coverage, and temporal resolution.
- Exploratory analysis - Visualize spatial and temporal patterns. Plot time series for trends, anomalies, and seasonal decomposition. Map spatial distributions using appropriate projections.
- Statistical modeling - Apply trend analysis (Mann-Kendall, Sen's slope for non-parametric trends). Use regression models for exposure-response relationships. For ecological data: species distribution models (MaxEnt, random forests), diversity indices (Shannon, Simpson).
- Impact assessment - Quantify environmental impact using standard metrics: carbon equivalent (tCO2e), air quality index (AQI), water quality index (WQI), ecological footprint. Compare against regulatory thresholds (EPA NAAQS, WHO guidelines).
- Scenario analysis - Model future projections under different scenarios (RCP/SSP pathways for climate, land-use change scenarios). Conduct sensitivity analysis on key parameters.
- Communication - Present findings with clear maps, time series, and comparison to baselines. Translate technical results into policy-relevant language.
Key Databases and Tools
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 8d ago First seen · 53 lines · 44 tokens per session scan A d887ebfd4e33
environmental-science is a skill published in the GitHub repository beita6969/ScienceClaw (898 stars, last pushed 3mo ago), licensed MIT. It adds 44 tokens to every session and 697 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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biomcp
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biomcp-research
Do biomedical literature and variant research with the BioMCP CLI, and file what you learn about the tool itself as issues in the biomcp repo.
biological-expert
Expert-level biology, biotechnology, genetics, bioinformatics, and computational biology. Use when the user mentions biology, biotechnology, genetics, bioinformatics, or genomics, or when the task involves Molecular Biology, Genomics & Bioinformatics, Systems Biology, or Data Analysis.