ml4t-evaluate-factor SKILL.md skillA
ml4t-evaluate-factor 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-evaluate-factor@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
validation/evaluate-factor/SKILL.md- Versions recorded
- 2
- Latest version
- git:20260901.c415df0, committed Sep 1, 2026
- First version recorded
- May 28, 2026
- Size
- 4,748 bytes
- Repository stars
- 41
- License
- Apache-2.0
Evaluate alpha factor quality with IC analysis, quantile spreads, turnover, and decay. Use when deciding whether a signal has enough predictive power to trade.
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
# Factor Evaluation
A factor that looks predictive may be untradeable due to high turnover, rapid decay, or non-monotonic quantile spreads. Comprehensive evaluation before portfolio integration prevents costly live failures.
## The Problem
Reporting a single backtest Sharpe ratio conflates signal quality with portfolio construction. A factor with IC 0.03 and low turnover can be more valuable than one with IC 0.05 and 80% daily turnover - whether IC is sufficient depends on breadth, turnover costs, and regime stability. Without decomposing signal quality into IC, quantile monotonicity, turnover, and decay, you cannot diagnose why a strategy fails or how to improve it.
## The Pattern
### WRONG
```python
# Evaluate only via backtest Sharpe - hides factor-level issues
returns = run_backtest(signal)
sharpe = returns.mean() / returns.std() * np.sqrt(252)
print(f"Sharpe: {sharpe:.2f}") # No idea why it works or doesn't
```
### CORRECT
```python
import numpy as np
from scipy import stats
# 1. Information Coefficient: rank correlation with forward returns
def compute_ic_series(signal, forward_returns, timestamps):
"""Per-period rank IC between signal and forward returns."""
…Read the whole file at its exact version.
How to install
mdr add ml4t/skills/ml4t-evaluate-factor@sha256:2919eb8dc6215dc8The 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_useqyvaln4mih7v7)
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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 | 4,748 B | A | view · diff |
| git:20260528.303089e | 2026-05-28 | 303089e | 4,758 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 (4748 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_useqyvaln4mih7v7 GET https://markdownregistry.com/api/v1/resolve?ref=ml4t/skills/ml4t-evaluate-factor GET https://markdownregistry.com/api/v1/blob/2919eb8dc6215dc8681d84d3a25ba671f78d54d537271863838164fa5f63cbbe
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.