ml4t-rl-execution SKILL.md skillA
ml4t-rl-execution 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-rl-execution@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
backtest/rl-execution/SKILL.md- Versions recorded
- 2
- Latest version
- git:20260901.c415df0, committed Sep 1, 2026
- First version recorded
- May 28, 2026
- Size
- 4,706 bytes
- Repository stars
- 41
- License
- Apache-2.0
Reinforcement learning for trade execution and hedging. Use when optimizing execution algorithms or dynamic hedging policies.
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
# RL for Trade Execution
Fixed execution schedules (TWAP, VWAP) ignore real-time market conditions. An RL agent adapts its execution rate based on order book state, reducing implementation shortfall.
## The Problem
Executing a large order at a fixed rate creates predictable market impact. A 100K-share TWAP sell ignores favorable liquidity bursts and pushes through thin books. The result: 20-50 bps of avoidable shortfall on institutional orders, compounding across thousands of trades per year.
## The Pattern
Model execution as a finite-horizon MDP. State: remaining shares, time left, volume, spread. Action: execution rate. Reward: negative implementation shortfall.
### WRONG
```python
# Static TWAP - ignores market conditions entirely
def twap_execute(total_shares: int, n_slices: int) -> list[int]:
base = total_shares // n_slices
remainder = total_shares % n_slices
return [base + (1 if i < remainder else 0) for i in range(n_slices)]
schedule = twap_execute(100_000, 20) # Same size every slice, blind to liquidity
```
### CORRECT
```python
import gymnasium as gym
import numpy as np
from gymnasium import spaces
class ExecutionEnv(gym.Env):
…Read the whole file at its exact version.
How to install
mdr add ml4t/skills/ml4t-rl-execution@sha256:c3920babfac6f2edThe 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_mspmjfli56vfwxox)
2 badge image fetches in 30 days. What the badge shows.
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 | 4,706 B | A | view · diff |
| git:20260528.303089e | 2026-05-28 | 303089e | 4,718 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 (4706 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_mspmjfli56vfwxox GET https://markdownregistry.com/api/v1/resolve?ref=ml4t/skills/ml4t-rl-execution GET https://markdownregistry.com/api/v1/blob/c3920babfac6f2ed718615f8a6505e7e41c450dbcc1324633d3cbe99e5e5b9ab
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.