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.
git 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/commands/steadfastasart/geoscience-skills/seismic-workflow)<a href="https://agentmods.dev/commands/steadfastasart/geoscience-skills/seismic-workflow"><img src="https://agentmods.dev/badge/commands/steadfastasart/geoscience-skills/seismic-workflow.svg" alt="Measured on agentmods" 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 | $0.00011 | $0.00450 |
| Opus 5 | $0.00005 | $0.00225 |
| Sonnet 5 | $0.00002 | $0.00090 |
| Haiku 4.5 | $0.00001 | $0.00045 |
Grade A, and why
seismic-workflow 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.
What it actually says
Seismic Data Analysis Workflow
Guide the user through a seismic data analysis pipeline. Determine the appropriate skill chain based on their data and goals.
Decision Tree
-
What format is the data?
- SEG-Y (.sgy, .segy) → Use
segyioskill for loading - MiniSEED / SAC / other seismological formats → Use
obspyskill for loading - Already loaded as numpy array → Skip to processing
- SEG-Y (.sgy, .segy) → Use
-
What processing is needed?
- Filtering, detrending, spectral analysis → Use
obspyskill - Rock physics (AVO, fluid substitution, elastic moduli) → Use
brugesskill - Surface wave dispersion → Use
disbaskill
- Filtering, detrending, spectral analysis → Use
-
Visualization needs?
- 2D section / wiggle plots → matplotlib (built-in)
- 3D seismic volume rendering → Use
pyvistaskill
Skill Chain
segyio (load SEG-Y) → obspy (signal processing) → bruges (rock physics) → pyvista (3D viz)
↘ disba (dispersion)
Step Prompts
For each step, invoke the relevant domain skill and follow its guidance.
Step 1: Data Loading
- Load seismic data and inspect geometry
- Check trace headers, inline/crossline ranges
- Validate sample rate and trace length
Step 2: Quality Control
- Check for dead traces and amplitude anomalies
- Validate geometry consistency
- Review amplitude statistics
Step 3: Processing
- Apply filters (bandpass, notch) as needed
- Detrend and remove DC offset
- Apply gain corrections if needed
Step 4: Analysis
- Rock physics: AVO analysis, fluid substitution
- Surface waves: compute dispersion curves
- Attributes: amplitude, phase, frequency
Step 5: Visualization
- 2D: seismic sections, amplitude maps
- 3D: volume rendering, horizon surfaces
$ARGUMENTS
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 · 61 lines · 11 tokens per session scan A 41be00047862
seismic-workflow is a command published in the GitHub repository SteadfastAsArt/geoscience-skills (57 stars, last pushed 5mo ago), licensed MIT. It adds 11 tokens to every session and 450 once invoked, about $0.0001 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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specify
Create or update the feature specification from a natural language feature description.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.