cxcscmu/skilllearnbench/glm-calibrator
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Calibrate GLM by adjusting key parameters to minimize RMSE. Use this skill when you need to iteratively tune model parameters to meet performance thresholds.
Install
npx vskill@latest install cxcscmu/skilllearnbench/glm-calibratorSKILL.md
GLM Calibrator Skill
Calibration Strategy
- Baseline Run: Start with the original
glm3.nmlparameters. - Sensitivity Analysis: Understand how
Kw,coef_mix_hyp,wind_factor,lw_factor, andchaffect simulation results (e.g.,Kwaffects deep temperatures). - Iteration Loop:
- Adjust one or more parameters within the allowed ranges.
- Run the simulation using
glm-runner. - Evaluate performance using
glm-evaluator. - Repeat until all three RMSE checks are satisfied:
overall_rmse < 1.60annual_deep_rmse < 1.55summer_deep_rmse < 1.70
- Parameter Ranges:
Kw: [0.1, 0.5]coef_mix_hyp: [0.3, 0.7]wind_factor: [0.7, 1.3]lw_factor: [0.7, 1.3]ch: [0.0005, 0.002]
Key Calibration Targets
Kw: Light extinction coefficient (higherKwleads to cooler deep waters).wind_factor: Scaling factor for wind speed (affects surface mixing).coef_mix_hyp: Scaling factor for hypolimnetic mixing.lw_factor: Scaling factor for longwave radiation.ch: Bulk transfer coefficient for sensible heat.
Security
- Security scanPassed, 90 of 100Pattern checks on the skill's files.
- Model reviewPassed
Quality evaluation
- Task evaluationNot runNo evaluation yet. Run one in Skill Studio.
Source
- SKILL.md in the repositoryCheckingskills/b4-skill-creator-gemini-3-flash-preview/temperature-simulation/glm-calibrator/SKILL.md
Popularity
- Repository stars
- 83
- Repository forks
- 7
- 7-day trend score
- 27
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