netcdf-analysis SKILL.md skillA
netcdf-analysis from cxcscmu/skilllearnbench is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.
mdr add cxcscmu/skilllearnbench/netcdf-analysis@git:20260424.d50cf5aPins git:20260424.d50cf5a in mdr.lock. Pin the fingerprint instead.
- Audit grade
- A, 17 of 17 checks passed
- Kind
- SKILL.md skill
- Repository
- cxcscmu/skilllearnbench
- Path
skills/b1-one-shot-claude-opus-4-6/temperature-simulation/netcdf-analysis/SKILL.md- Versions recorded
- 1
- Latest version
- git:20260424.d50cf5a, committed Apr 24, 2026
- Size
- 1,199 bytes
- Repository stars
- 91
- License
- MIT
Reading and analyzing GLM NetCDF output with Python netCDF4 and pandas for RMSE evaluation.
Collected from public GitHub. Every version is saved exactly as it was and never changes. Install it at an exact version with the mdr tool, and every file is checked before it reaches your agent. The main file is checked against the SHA-256 fingerprint recorded here, and the others against the fingerprints GitHub keeps for its source commit. The automatic checks below grade the latest version, and the same checks always give the same file the same grade.
What the file says
# NetCDF Analysis for GLM Output
## Reading GLM Output
```python
import netCDF4 as nc
import numpy as np
import pandas as pd
ds = nc.Dataset('output/output.nc')
temp = ds.variables['temp'][:] # masked array [time, layers]
z = ds.variables['z'][:] # height above bottom [time, layers]
time_var = ds.variables['time']
times = nc.num2date(time_var[:], time_var.units)
```
## Extracting Temperature at Specific Depths
GLM uses variable layer heights. For each timestep:
```python
lake_depth = 25 # from morphometry (crest_elev - min(H))
for t in range(len(times)):
valid = ~temp[t].mask if hasattr(temp[t], 'mask') else np.ones(temp.shape[1], bool)
depths_from_surface = lake_depth - z[t, valid]
temps = temp[t, valid]
# Interpolate to desired depth
```
## RMSE Calculation
```python
# Merge on exact datetime and rounded depth
# rmse = sqrt(mean((obs - sim) ** 2))
```
## Key Notes
- GLM z is height from lake bottom; depth = lake_depth - z
- Round depths to nearest integer for matching
- Use exact datetime matching (no nearest-time)Read the whole file at its exact version.
How to install
mdr add cxcscmu/skilllearnbench/netcdf-analysis@sha256:596b94c00cd4ae55The line at the top of this page pins the label git:20260424.d50cf5a, which is what most people want. This one pins the sha256 fingerprint of the contents instead, so it survives a label being moved. Either way the exact version is written to mdr.lock, and mdr install downloads and checks those contents again, so it installs them exactly or stops with an error.
[](https://markdownregistry.com/a/art_oaq2vpqtoptl5dql)
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Versions
The registry has recorded 1 version of this file, committed on Apr 24, 2026.
Audit of the latest version
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- pass: No credential-shaped string
- pass: No instruction to send local credentials anywhere
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- pass: No curl or wget piped into a shell
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Source
cxcscmu/skilllearnbench · 91 stars · license MIT · pushed 2026-10-02 · branch main
API
GET https://markdownregistry.com/api/v1/artifacts/art_oaq2vpqtoptl5dql GET https://markdownregistry.com/api/v1/resolve?ref=cxcscmu/skilllearnbench/netcdf-analysis GET https://markdownregistry.com/api/v1/blob/596b94c00cd4ae5518937bcdd627c76037f4b144cecffa7b42c7c036f3a53d09
Your AI assistant does the legwork. You hear about the deals worth your word. Hand yours the standing instructions at modelranch.com and it joins the network that reads files like this one.
Guides: the SKILL.md format and its required fields · what to check before you install a skill · how to pin a skill to an exact version · where to find agent skills · keeping a team on the same skills · which agent file does what.