A specialized reasoning layer for AI agents that enforces rigorous physics-based grounding and epistemic clarity in Earth sciences and subsurface data analysis.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install geox-ground
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install geox-ground using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is GEOX Ground?
GEOX Ground is a technical grounding layer designed to force AI agents to reason through physics, material constraints, and real-world data when handling tasks related to the physical Earth. By utilizing these Openclaw Skills, users can transform standard LLM outputs into rigorous technical evaluations that prioritize material reality over elegant narrative fiction. It acts as a Large Earth Model layer, ensuring that every claim made about the subsurface is anchored in verifiable data and logical physical constraints.
The core value of GEOX Ground lies in its ability to prevent hallucination in high-stakes environments like energy, mining, and civil engineering. By implementing a strict separation between observation and interpretation, this skill ensures that Openclaw Skills remain reliable tools for experts who require precise, data-backed reasoning rather than generalized summaries.
GEOX Ground Use Cases
- Interpreting complex seismic data and well logs with explicit epistemic labeling.
- Evaluating reservoir potential by prioritizing physical seal capacity over narrative descriptions.
- Performing formation evaluation and petrophysical analysis with mandated uncertainty ranges.
- Conducting basin modeling and structural geology assessments where data grounding is critical.
- Standardizing technical communication between AI agents and human geoscientists using Openclaw Skills.
How GEOX Ground Works
- The skill monitors for Earth-domain triggers such as keywords related to geology, petrophysics, or reservoir engineering.
- Upon activation, the agent is forced to adopt the GEOX Habit, which mandates the separation of epistemic levels for every claim.
- All data inputs are categorized into direct observations (OBS), derived data (DER), interpretations (INT), or speculations (SPEC).
- The reasoning engine applies physics-first rules, ensuring that material constraints (like fluid pressure or rock strength) dictate the validity of the output.
- The agent applies uncertainty bands to all quantitative values and flags any areas where data is insufficient to reach a confident conclusion.
GEOX Ground Setup
To activate GEOX Ground within your existing agent environment, you must include the skill definition in your configuration files. For users managing their setup via terminal, follow these steps to integrate these Openclaw Skills:
# Install the GEOX Ground reasoning module
openclaw install geox-ground
# Map the reference documents for epistemic labeling
openclaw link ./references/epistemic-labels.md --as geo-logic
GEOX Ground Data Schema & Taxonomy
GEOX Ground utilizes a structured epistemic taxonomy to organize geoscience data and metadata. This ensure that all Openclaw Skills maintain a clear audit trail from raw data to final interpretation.
| Taxonomy Label | Data Type | Requirement |
|---|---|---|
| OBS | Observation | Must cite a direct measurement or source log. |
| DER | Derived | Must provide the calculation or logic used to transform raw data. |
| INT | Interpretation | Must be supported by OBS or DER data points. |
| SPEC | Speculation | Used for high-uncertainty scenarios where data is missing. |
GEOX Ground Advanced Features
- Physics-over-narrative enforcement that rejects physically impossible geological interpretations.
- Automated uncertainty band generation for all quantitative subsurface claims.
- Explicit hold conditions that pause reasoning when critical data points are absent.
- Seamless integration with other Openclaw Skills for multi-disciplinary engineering workflows.
- Anti-error pattern recognition to prevent false precision and overconfidence in speculative models.
SKILL.md
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