model-calibration SKILL.md skillA
model-calibration 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/model-calibration@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-haiku-4-5/temperature-simulation/model-calibration/SKILL.md- Versions recorded
- 1
- Latest version
- git:20260424.d50cf5a, committed Apr 24, 2026
- Size
- 5,124 bytes
- Repository stars
- 91
- License
- MIT
Calculating RMSE metrics and parameter calibration for lake model validation.
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
# Model Calibration Skill
## Overview
Model calibration involves adjusting parameters to minimize differences between simulations and observations. RMSE (Root Mean Squared Error) is a standard metric for measuring model performance.
## RMSE Calculation
### Basic Formula
```
RMSE = sqrt(mean((simulated - observed)^2))
```
### Implementation
```python
import numpy as np
import pandas as pd
def calculate_rmse(simulated, observed):
"""Calculate RMSE between matched pairs"""
if len(simulated) == 0:
return np.nan
residuals = simulated - observed
rmse = np.sqrt(np.mean(residuals**2))
return rmse
def calculate_metrics(sim_temps, obs_temps, depths=None, dates=None):
"""
Calculate multiple RMSE metrics
Parameters:
- sim_temps: matched simulated temperatures
- obs_temps: matched observed temperatures
- depths: depth of each match (for deep water filtering)
- dates: datetime of each match (for seasonal filtering)
Returns:
- overall_rmse: RMSE of all matched pairs
- annual_deep_rmse: RMSE of pairs at depths >= 13m
- summer_deep_rmse: RMSE of summer (Jun-Sep) pairs at depths >= 13m
"""
…Read the whole file at its exact version.
How to install
mdr add cxcscmu/skilllearnbench/model-calibration@sha256:3c900ee5a3acf933The 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_emkirwvfgbk6bunc)
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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: Frontmatter declares a name
- pass: Frontmatter declares a description
- pass: Size between 200 bytes and 200 KB (5124 bytes)
- pass: No zero-width or bidi control characters
- pass: No instruction hidden inside an HTML comment
- pass: No link to an exfiltration or paste host
- pass: No credential-shaped string
- pass: No instruction to send local credentials anywhere
- pass: No text hidden with inline styles
- pass: No prompt-injection phrasing
- pass: No curl or wget piped into a shell
- pass: No recursive delete of root, home or parent
- pass: No instruction to read or print local credentials
- pass: No base64 blob over 200 characters
- pass: No link to a raw IP address
- pass: No script tag
Source
cxcscmu/skilllearnbench · 91 stars · license MIT · pushed 2026-10-02 · branch main
API
GET https://markdownregistry.com/api/v1/artifacts/art_emkirwvfgbk6bunc GET https://markdownregistry.com/api/v1/resolve?ref=cxcscmu/skilllearnbench/model-calibration GET https://markdownregistry.com/api/v1/blob/3c900ee5a3acf933ac76316df716cd08d611554f7c0dd39f2f56f5e9a33fb43f
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.