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sertug17

Gearbox

by Sertug17 · GitHub ↗ · v1.0.0
cross-platform ✓ Security Clean
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Install in OpenClaw
/install gearbox
Description
Assesses wind turbine gearbox health from multi-sensor and inspection data. Classifies damage severity (1-5), identifies root cause, and recommends shutdown...
README (SKILL.md)

Wind Turbine Gearbox Intelligence

Evaluates gearbox condition using five input parameters and produces a structured maintenance report.

When to Use

Load this skill when the user wants to:

  • Assess gearbox health from on-site inspection or sensor data
  • Classify damage severity on a 1-5 scale
  • Determine whether a turbine should be shut down or kept running under monitoring
  • Generate a structured maintenance or escalation plan

Quick Reference

Input Parameter What to Collect
Visual inspection Surface cracks, pitting, spalling, discoloration, debris
Oil iron (Fe ppm) Iron particle concentration in gear oil (ppm)
Temperature (C) Bearing/gear temperature, normalized to baseline
Vibration RMS or peak-to-peak acceleration (g), frequency anomalies
Acoustic / Sound Noise type: grinding, knocking, whining, clicking

Fault Thresholds (Reference)

Parameter Normal Warning Critical
Oil Fe (ppm) \x3C 100 100 - 300 > 300
Temp above baseline \x3C 5 C 5 - 15 C > 15 C
Vibration RMS (g) \x3C 0.5 0.5 - 1.5 > 1.5
Acoustic No anomaly Intermittent Continuous
Visual Clean surface Minor pitting Spalling/crack

Common Failure Modes

Failure Mode Typical Indicators
Micropitting High Fe ppm, slight vibration increase, no visible cracks
Spalling High Fe ppm, elevated vibration, visible surface damage
Fatigue crack Knocking sound, vibration spike at gear mesh frequency
Bearing wear Whining noise, high temperature, broadband vibration increase
Oil contamination Very high Fe ppm, discolored oil, possible foaming

Procedure

  1. Collect inputs across all five parameters. If any are unavailable, note as "not measured" and proceed.
  2. Evaluate each parameter against the thresholds table. Flag Warning or Critical zones.
  3. Cross-correlate symptoms:
    • Fe ppm + vibration increase → wear / spalling progression
    • Knocking sound + vibration spike → fatigue crack
    • Temperature + whining sound → bearing failure
    • Multiple Critical flags → Severity 5
  4. Assign severity:
    • 1 Healthy: All parameters normal. No action required.
    • 2 Early wear: 1-2 parameters in warning zone. Increase monitoring frequency.
    • 3 Moderate damage: 2-3 parameters in warning/critical. Inspect within 2 weeks.
    • 4 Significant damage: Multiple critical flags. Plan shutdown within 48-72 hours.
    • 5 Critical: Imminent failure risk. Immediate shutdown required.
  5. Determine root cause from the failure modes table.
  6. Generate the output report using the format below.

Output Format

=== GEARBOX HEALTH REPORT ===

ROOT CAUSE : [e.g., Progressive spalling on intermediate shaft gear] SEVERITY : [1-5] - [Healthy / Early Wear / Moderate / Significant / Critical] SHUTDOWN : [Yes / No / Conditional]

MONITORING STRATEGY:

  • [e.g., Repeat oil sample in 72 hours]
  • [e.g., Daily vibration trend monitoring for 1 week]

ESCALATION TRIGGERS:

  • [e.g., Fe ppm exceeds 400 - immediate shutdown]
  • [e.g., Vibration RMS exceeds 2.0 g - immediate shutdown]

Pitfalls

  • Never assign Severity 5 based on one parameter alone. Cross-validate with at least two sources.
  • Temperature readings can be misleading in extreme ambient conditions. Ask for baseline-normalized values.
  • Acoustic descriptions are subjective. Ask for noise type and whether continuous or intermittent.
  • If sensor data is unavailable, rely on visual and oil condition as primary indicators.
  • Do not conflate oil change interval with oil health. New oil can still show high Fe ppm.

Verification

After generating the report, confirm with the user:

  • Does the severity match their on-site observations?
  • Are escalation thresholds feasible for their monitoring setup?
  • Are there additional data points (CMS trending, historical Fe ppm) that could refine the assessment?
Usage Guidance
This is a text-only diagnostic recipe (no code or external installs), so the technical risk is low. Before relying on it in operations, confirm the threshold values and escalation triggers match your OEM/vendor guidance and your sensors' calibration; treat its shutdown recommendations as advisory and verify with on-site engineers before executing critical actions. Also confirm any automated workflows that consume this report include human review—this skill itself does not request credentials or system access, but automated actuation based on its output should be gated.
Capability Analysis
Type: OpenClaw Skill Name: gearbox Version: 1.0.0 The skill bundle contains standard metadata and a `SKILL.md` file that provides clear, domain-specific instructions for an AI agent to assess wind turbine gearbox health. The instructions focus on data analysis, classification, and report generation, without any indication of malicious intent, prompt injection attempts, or instructions that would lead to unauthorized actions, data exfiltration, or system compromise. All content aligns with the stated purpose of a diagnostic tool.
Capability Assessment
Purpose & Capability
Name and description match the SKILL.md: it is a diagnostic checklist and report formatter for gearbox health. No unrelated credentials, binaries, or installs are requested.
Instruction Scope
Runtime instructions are limited to collecting five sensor/inspection inputs, comparing them to thresholds, correlating symptoms, and producing a structured report. The instructions do not ask to read system files, environment variables, or transmit data to external endpoints.
Install Mechanism
No install spec and no code files—this is instruction-only, so nothing is downloaded or written to disk. This is the lowest-risk install profile.
Credentials
No environment variables, credentials, or config paths are required. The requested inputs (visual, oil Fe, temp, vibration, acoustic) are appropriate for the stated diagnostic purpose.
Persistence & Privilege
The skill is not always-enabled and does not request persistent/system-wide changes. It does not ask to modify other skills or agent configuration.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install gearbox
  3. After installation, invoke the skill by name or use /gearbox
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
- Initial release of the wind-turbine-gearbox skill. - Evaluates wind turbine gearbox condition using multi-sensor and inspection data. - Classifies damage severity on a 1-5 scale based on five key parameters. - Identifies likely root cause from typical failure modes. - Recommends shutdown or enhanced monitoring actions in a structured report format. - Includes clear input guidelines, threshold tables, and verification steps.
Metadata
Slug gearbox
Version 1.0.0
License
All-time Installs 0
Active Installs 0
Total Versions 1
Frequently Asked Questions

What is Gearbox?

Assesses wind turbine gearbox health from multi-sensor and inspection data. Classifies damage severity (1-5), identifies root cause, and recommends shutdown... It is an AI Agent Skill for Claude Code / OpenClaw, with 332 downloads so far.

How do I install Gearbox?

Run "/install gearbox" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is Gearbox free?

Yes, Gearbox is completely free (open-source). You can download, install and use it at no cost.

Which platforms does Gearbox support?

Gearbox is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created Gearbox?

It is built and maintained by Sertug17 (@sertug17); the current version is v1.0.0.

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