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 near-surface-geophysicsgit 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/near-surface-geophysics)<a href="https://agentmods.dev/skills/steadfastasart/geoscience-skills/near-surface-geophysics"><img src="https://agentmods.dev/badge/skills/steadfastasart/geoscience-skills/near-surface-geophysics/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/near-surface-geophysics"><img src="https://agentmods.dev/badge/skills/steadfastasart/geoscience-skills/near-surface-geophysics.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 | $0.00056 | $0.01511 |
| Opus 5.5 | $0.00022 | $0.00604 |
| Sonnet 5.5 | $0.00011 | $0.00302 |
| Haiku 4.5 | $0.00006 | $0.00151 |
Grade A, and why
near-surface-geophysics 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 — 133 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Near-Surface Geophysics
Select only branches supported by the supplied data. This is a single-agent workflow; companion skills are optional references, and a missing GPR or MT dataset does not prevent an ERT-only interpretation.
Input-dependent routes
| Input | Start with | Required checks before interpretation |
|---|---|---|
| GPR traces and acquisition geometry | gprpy |
Trace order/spacing, sample-time units, time zero, antenna offsets and an independently supported velocity model |
| ERT electrode geometry and measurements | pygimli |
Electrode indexing, measured quantities, geometric factors, uncertainty/reciprocals and topography |
| MT transfer functions or EDI files | mtpy |
Frequency coverage, impedance units and convention, rotations, tensor components and uncertainty |
| Multiple methods with compatible survey support | Process each branch independently, then compare | Common CRS/vertical reference, resolution, uncertainty and acquisition timing |
If only an image is available, state which quantitative operations require raw data or survey metadata. Do not infer a complete inversion dataset from colours or an unlabelled axis. Check package version and file-reader support before choosing a library-specific implementation.
Shared preparation
Retain raw files and acquisition metadata with checksums. Establish horizontal CRS, elevation datum, profile direction, measurement units and sign conventions. Keep instrument flags and a record of excluded readings. Describe the physical question and independent borehole, geological or hydrological constraints before tuning an image or model to resemble an expected structure.
GPR branch
Inspect unprocessed radargrams first. Apply time-zero correction only when a justified reference is available, and select documented signal processing; compare each step to the input. Record filter bands relative to sample interval and antenna bandwidth. Gain changes amplitude interpretation, and background removal can suppress genuine laterally continuous reflectors. Preserve original amplitudes when an amplitude comparison is required.
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 · 133 lines · 56 tokens per session scan A d9367dab735e
near-surface-geophysics is a skill published in the GitHub repository SteadfastAsArt/geoscience-skills (70 stars, last pushed 1mo ago), licensed MIT. It adds 56 tokens to every session and 1,511 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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