ml4t-production-readiness skillA
ml4t-production-readiness is agent-read markdown (skill) from ml4t/skills: Pre-deployment checklist covering data pipelines, risk limits, monitoring, and governance. Use when preparing to go live with a new strategy or model..
Indexed from public GitHub and served as immutable, content-addressed versions. Install it pinned to an exact SHA-256 with the mdr CLI, and every file is verified against the hash recorded here before it reaches your agent. The deterministic audit below grades the latest version, and the same file always earns the same grade.
What the file says
# Production Readiness
A validated backtest is not a production system. The gap between "model works" and "strategy can run unattended with real money" requires infrastructure that most teams skip until the first incident.
## The Problem
A team deploys a model that passed validation. On day three, the data vendor has an outage. The model receives stale prices, generates signals, and the execution system submits orders on bad data. There is no kill switch, no staleness check, no alert. By the time someone notices, the strategy has lost two months of expected returns in a single session. Every production failure traces back to missing infrastructure, not bad models.
## The Pattern
### WRONG
```python
# Model works in backtest - deploy directly
import pickle
from broker_api import submit_orders
model = pickle.load(open("best_model.pkl", "rb"))
data = fetch_latest_data()
signals = model.predict(data)
orders = signals_to_orders(signals)
for order in orders:
submit_orders(order) # No limits, no monitoring, no kill switch
```
### CORRECT
```python
# Five infrastructure layers before any live order
import datetime as dt
…Read the whole file at its exact version.
How to install
mdr add ml4t/skills/ml4t-production-readiness@git:20260901.297789fmdr add ml4t/skills/ml4t-production-readiness@sha256:56d9e3792568120ePin to a label to follow the author's releases, or to a sha256 to freeze the exact bytes forever. Either way the resolved hash is written to mdr.lock, and mdr install reproduces it on any machine.
[](https://markdownregistry.com/a/art_4irytoodfsqyj45h)
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Versions
| version | committed | commit | size | audit | |
|---|---|---|---|---|---|
| git:20260901.297789f latest | 2026-09-01 | 297789f | 5,857 B | A | view · diff |
| git:20260901.4a67198 | 2026-09-01 | 4a67198 | 5,830 B | A | view · diff |
| git:20260901.85fc79b | 2026-09-01 | 85fc79b | 5,811 B | A | view · diff |
| git:20260901.c415df0 | 2026-09-01 | c415df0 | 5,747 B | A | view · diff |
| git:20260528.303089e | 2026-05-28 | 303089e | 5,761 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 (5857 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 · 19 stars · license Apache-2.0 · pushed 2026-09-24 · branch main
API
GET https://markdownregistry.com/api/v1/artifacts/art_4irytoodfsqyj45h GET https://markdownregistry.com/api/v1/resolve?ref=ml4t/skills/ml4t-production-readiness GET https://markdownregistry.com/api/v1/blob/56d9e3792568120ec7e7eae997d1d8da20f3dc1fa0ffac016653fc6bdb0e0dfd
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