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 disbagit 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/disba)<a href="https://agentmods.dev/skills/steadfastasart/geoscience-skills/disba"><img src="https://agentmods.dev/badge/skills/steadfastasart/geoscience-skills/disba/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/disba"><img src="https://agentmods.dev/badge/skills/steadfastasart/geoscience-skills/disba.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 | $0.00098 | $0.01446 |
| Opus 5 | $0.00049 | $0.00723 |
| Sonnet 5 | $0.00020 | $0.00289 |
| Haiku 4.5 | $0.00010 | $0.00145 |
Grade A, and why
disba 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 9d 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 — 162 lines — stays where its author put it; the contents beside it link to each section on GitHub.
disba - Surface Wave Dispersion
Quick Reference
import numpy as np
from disba import PhaseDispersion, GroupDispersion
# Define velocity model (thickness, Vp, Vs, density)
# thickness in km, velocities in km/s, density in g/cm3
thickness = np.array([0.5, 1.0, 2.0, 0.0]) # 0.0 = half-space
vp = np.array([1.5, 2.5, 4.0, 6.0])
vs = np.array([0.8, 1.4, 2.3, 3.5])
rho = np.array([1.8, 2.0, 2.3, 2.6])
# Periods to compute (seconds)
periods = np.linspace(0.1, 5.0, 50)
# Calculate Rayleigh wave phase velocity
pd = PhaseDispersion(*zip(thickness, vp, vs, rho))
cpr = pd(periods, mode=0, wave='rayleigh') # Fundamental mode
# Calculate group velocity
gd = GroupDispersion(*zip(thickness, vp, vs, rho))
ugr = gd(periods, mode=0, wave='rayleigh')
Key Classes
| Class | Purpose |
|---|---|
PhaseDispersion |
Phase velocity dispersion curves |
GroupDispersion |
Group velocity dispersion curves |
PhaseSensitivity |
Sensitivity kernels (dc/dVs, dc/dVp, dc/drho) |
Essential Operations
Rayleigh and Love Waves
pd = PhaseDispersion(*zip(thickness, vp, vs, rho))
cpr = pd(periods, mode=0, wave='rayleigh') # Vertical + radial motion
cpl = pd(periods, mode=0, wave='love') # Horizontal SH motion
Multiple Modes
for mode in range(3): # Fundamental + higher modes
try:
cpr = pd(periods, mode=mode, wave='rayleigh')
except Exception:
pass # Higher modes may not exist at all periods
Sensitivity Kernels
from disba import PhaseSensitivity
ps = PhaseSensitivity(*zip(thickness, vp, vs, rho))
kernel_vs = ps(period=1.0, mode=0, wave='rayleigh', parameter='velocity_s')
# Other parameters: 'velocity_p', 'density'
Forward Modelling
def forward_model(vs_profile, thickness, vp_vs_ratio=1.73):
"""Compute dispersion curve from Vs profile."""
vp = vs_profile * vp_vs_ratio
rho = 0.32 * vp + 0.77 # Gardner relation
pd = PhaseDispersion(*zip(thickness, vp, vs_profile, rho))
return pd(periods, mode=0, wave='rayleigh')
What ships with it
3 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.
- 9d ago First seen · 162 lines · 98 tokens per session scan A 48f2fef58f83
disba is a skill published in the GitHub repository SteadfastAsArt/geoscience-skills (57 stars, last pushed 5mo ago), licensed MIT. It adds 98 tokens to every session and 1,446 once invoked, about $0.0005 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 2026-08-30.
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