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 SteadfastAsArt/geoscience-skills --skill hydrogeological-analysisgit clone --depth 1 https://github.com/SteadfastAsArt/geoscience-skillsWrote 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/steadfastasart/geoscience-skills/hydrogeological-analysis)<a href="https://agentmods.dev/skills/steadfastasart/geoscience-skills/hydrogeological-analysis"><img src="https://agentmods.dev/badge/skills/steadfastasart/geoscience-skills/hydrogeological-analysis/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/steadfastasart/geoscience-skills/hydrogeological-analysis"><img src="https://agentmods.dev/badge/skills/steadfastasart/geoscience-skills/hydrogeological-analysis.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00055 | $0.01446 |
| Opus 5.5 | $0.00022 | $0.00578 |
| Sonnet 5.5 | $0.00011 | $0.00289 |
| Haiku 4.5 | $0.00006 | $0.00145 |
Grade A, and why
hydrogeological-analysis 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 1mo 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 — 117 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Hydrogeological Analysis
Produce a traceable groundwater interpretation, then fit only the model the available observations can support. One agent can complete this workflow; companion skills provide optional detail. Install only the packages used by the chosen branch; FloPy is an optional spatial-flow branch.
Choose the branch
| Available information and question | Appropriate route |
|---|---|
| Logs, screen depths and construction records; no groundwater time series | Use lasio / welly for QC and a conceptual aquifer framework; do not invent a head calibration dataset. |
| Observed heads with precipitation, evaporation or pumping series | Use pastas for time-series response modelling and withheld-period validation. |
| Distributed heads, geometry, hydraulic properties, stresses and boundary conditions | Consider a FloPy/MODFLOW flow model; first specify the conceptual model and available executable. |
| Only sparse spatial observations | Map measurements with their observation dates and uncertainty; a verde interpolation is not a groundwater-flow solution. |
Establish observations and reference systems
- Identify each well, screen interval, measurement method, timestamp/timezone, pumping status, missing-value codes, units and quality flags. Preserve the original observations and a separate table of corrections/exclusions.
- Distinguish measured depth in a log, depth to water below a measuring point, and hydraulic head relative to a vertical datum. Convert depth to water using the surveyed measuring-point elevation and its reference; never treat a log depth column or well bottom as an observed head. Use trajectory and datum information before aligning deviated logs with aquifer elevations.
- Bring well positions, geology and model grids into a documented CRS. Record vertical datum and units separately. Do not merge different screened aquifers into one time series merely because their wells are nearby.
- Inspect stress coverage and sampling support. Distinguish accumulated rainfall from rates, and observed evaporation from the quantity expected by the chosen recharge model. Missing rainfall is not zero rainfall. Record any infilling and its source; require stress coverage through calibration and model warmup.
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 1mo ago First seen · 117 lines · 55 tokens per session scan A 9157802f9cc9
hydrogeological-analysis is a skill published in the GitHub repository SteadfastAsArt/geoscience-skills (70 stars, last pushed 1mo ago), licensed MIT. It adds 55 tokens to every session and 1,446 once invoked, about $0.0002 per session on Opus 5.5. 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 2026-09-16.
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