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 devitogit 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/devito)<a href="https://agentmods.dev/skills/steadfastasart/geoscience-skills/devito"><img src="https://agentmods.dev/badge/skills/steadfastasart/geoscience-skills/devito/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/devito"><img src="https://agentmods.dev/badge/skills/steadfastasart/geoscience-skills/devito.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 | $0.00120 | $0.01611 |
| Opus 5.5 | $0.00048 | $0.00644 |
| Sonnet 5.5 | $0.00024 | $0.00322 |
| Haiku 4.5 | $0.00012 | $0.00161 |
Grade A, and why
devito 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 — 174 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Devito - Symbolic PDE Solver
Quick Reference
from devito import Grid, Function, TimeFunction, Eq, solve, Operator
# Create grid
grid = Grid(shape=(101, 101), extent=(1000., 1000.))
# Velocity model
v = Function(name='v', grid=grid, space_order=4)
v.data[:] = 1500.
# Wavefield
p = TimeFunction(name='p', grid=grid, time_order=2, space_order=4)
# Wave equation: d2p/dt2 = v^2 * laplacian(p)
stencil = Eq(p.forward, solve(p.dt2 - v**2 * p.laplace, p.forward))
# Compile and run
op = Operator([stencil])
op(time_M=100, dt=0.5)
Key Classes
| Class | Purpose |
|---|---|
Grid |
Computational domain definition |
Function |
Spatial field on grid |
TimeFunction |
Time-dependent field |
SparseTimeFunction |
Point sources/receivers |
Operator |
Compiled computation kernel |
Essential Operations
Grid and Fields
from devito import Grid, Function, TimeFunction
# 2D/3D Grid
grid = Grid(shape=(nx, nz), extent=(x_size, z_size))
# Velocity model (spatial field)
v = Function(name='v', grid=grid, space_order=4)
v.data[:] = 1500.
# Wavefield (time-dependent)
p = TimeFunction(name='p', grid=grid, time_order=2, space_order=4)
Source and Receivers
from examples.seismic import RickerSource, Receiver, TimeAxis
time_range = TimeAxis(start=0., stop=1000., step=dt)
# Source
src = RickerSource(name='src', grid=grid, f0=10., npoint=1, time_range=time_range)
src.coordinates.data[0, :] = [500., 20.]
# Receivers
rec = Receiver(name='rec', grid=grid, npoint=101, time_range=time_range)
rec.coordinates.data[:, 0] = np.linspace(0., 1000., 101)
rec.coordinates.data[:, 1] = 20.
Build and Run
# Wave equation
stencil = Eq(p.forward, solve(p.dt2 - v**2 * p.laplace, p.forward))
src_term = src.inject(field=p.forward, expr=src * dt**2 * v**2)
rec_term = rec.interpolate(expr=p)
# Compile and execute
op = Operator([stencil] + src_term + rec_term)
op(time_M=nt-1, dt=dt)
# Results
shot_record = rec.data # (nt, nrec)
snapshot = p.data[0] # Current wavefield
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.
- 1mo ago Changed · +2 lines · +1 tokens per session 1cd642919d6f
- 2mo ago First seen · 172 lines · 119 tokens per session scan A 83b027495e54
devito is a skill published in the GitHub repository SteadfastAsArt/geoscience-skills (73 stars, last pushed 1mo ago), licensed MIT. It adds 120 tokens to every session and 1,611 once invoked, about $0.0005 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 2026-08-30.
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