ml4t-risk-metrics SKILL.md skillA
ml4t-risk-metrics from ml4t/skills is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.
mdr add ml4t/skills/ml4t-risk-metrics@git:20260901.c415df0Pins git:20260901.c415df0 in mdr.lock. Pin the fingerprint instead.
- Audit grade
- A, 17 of 17 checks passed
- Kind
- SKILL.md skill
- Repository
- ml4t/skills
- Path
portfolio/risk-metrics/SKILL.md- Versions recorded
- 2
- Latest version
- git:20260901.c415df0, committed Sep 1, 2026
- First version recorded
- May 28, 2026
- Size
- 4,121 bytes
- Repository stars
- 41
- License
- Apache-2.0
Compute portfolio risk measures including drawdown, VaR, CVaR, and tail metrics. Use when assessing portfolio risk beyond simple return statistics.
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
# Risk Metrics
A strategy with Sharpe 1.5 and max drawdown -55% will get shut down before it recovers. Reporting returns without drawdowns, tail risk, and duration metrics hides the path dependency that determines whether a strategy survives.
## The Problem
Sharpe ratio is the default performance metric, but it treats upside and downside volatility equally and says nothing about tail losses. A strategy can have a high Sharpe while hiding a -40% drawdown that takes 18 months to recover. Fund managers and allocators care about max drawdown, time underwater, and worst-case losses - because those determine whether the strategy (and the fund) survives. Always report drawdown alongside return metrics.
## The Pattern
### WRONG
```python
import numpy as np
returns = strategy_returns # daily
sharpe = returns.mean() / returns.std() * np.sqrt(252)
print(f"Sharpe: {sharpe:.2f}") # Looks great - ships it
```
### CORRECT
```python
import numpy as np
from scipy.stats import norm
returns = strategy_returns # daily, numpy array
# Return metrics
sharpe = returns.mean() / returns.std() * np.sqrt(252)
downside = np.minimum(returns, 0) # All returns: negative kept, positive → 0
…Read the whole file at its exact version.
How to install
mdr add ml4t/skills/ml4t-risk-metrics@sha256:6b1840c03b129627The line at the top of this page pins the label git:20260901.c415df0, 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_lc3veuziw5sqyfah)
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Versions
The registry has recorded 2 versions of this file, between May 28, 2026 and Sep 1, 2026, about one every 96 days.
| version | committed | commit | size | audit | |
|---|---|---|---|---|---|
| git:20260901.c415df0 latest | 2026-09-01 | c415df0 | 4,121 B | A | view · diff |
| git:20260528.303089e | 2026-05-28 | 303089e | 4,131 B | A | view |
Audit of the latest version
- pass: Frontmatter block present
- pass: Frontmatter declares a name
- pass: Frontmatter declares a description
- pass: Size between 200 bytes and 200 KB (4121 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
ml4t/skills · 41 stars · license Apache-2.0 · pushed 2026-11-08 · branch main
API
GET https://markdownregistry.com/api/v1/artifacts/art_lc3veuziw5sqyfah GET https://markdownregistry.com/api/v1/resolve?ref=ml4t/skills/ml4t-risk-metrics GET https://markdownregistry.com/api/v1/blob/6b1840c03b12962790f162434af701ea0178e6d093da9575c2d7d3e46aac2ca1
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.