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zenith-execution

Unified trade execution suite: Half-Kelly sizing, stop-loss calculation, Monte Carlo simulation, and portfolio rebalancing. Absorbs: kelly-mandate, stop-loss-calc, monte-carlo-sim, portfolio-rebalancer.

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ZenithFX Execution Suite (Expanded)

Absorbs: kelly-mandate, stop-loss-calc, monte-carlo-sim, portfolio-rebalancer

Unified quantitative execution skill for High Win-Rate trading systems (Protocol 367).

Triggers

"zenith", "trade setup", "position size", "stop loss", "kelly criterion", "how much to risk", "invalidation point", "simulate", "monte carlo", "rebalance", "portfolio allocation"

Sub-Commands

1. Position Sizing (Half-Kelly)

Demands Win Rate, Reward:Risk, and Total Capital.
Computes Full Kelly (theoretical optimum).
Halves it (Half-Kelly) for psychological variance and execution error.
Hard caps at 10% regardless of edge.

2. Stop-Loss (Structural Invalidation)

Identifies the price where the trade premise is demonstrably false.
Calculates distance between Entry and Invalidation.
Fits pre-determined Capital Risk % into that distance → Position Size.

Rule: A Stop Loss is a structural invalidation point, not an arbitrary budget allowance.

3. Monte Carlo Simulation

Simulates N independent trades through a given structure.

Inputs: Win Rate (%), Risk:Reward, Risk per trade (%), Number of trades (N), Starting capital.

import random

def monte_carlo(wr, rr, risk_pct, n_trades, starting_capital, n_paths=1000):
    results = []
    ruin_count = 0
    max_drawdowns = []
    for _ in range(n_paths):
        equity = starting_capital
        peak = equity
        max_dd = 0
        for _ in range(n_trades):
            if random.random() < wr:
                equity += equity * risk_pct * rr
            else:
                equity -= equity * risk_pct
            peak = max(peak, equity)
            dd = (peak - equity) / peak
            max_dd = max(max_dd, dd)
            if equity <= starting_capital * 0.2:
                ruin_count += 1
                break
        results.append(equity)
        max_drawdowns.append(max_dd)
    results.sort()
    return {
        "median": results[len(results)//2],
        "p5": results[int(len(results)*0.05)],
        "p95": results[int(len(results)*0.95)],
        "max_dd_median": sorted(max_drawdowns)[len(max_drawdowns)//2],
        "ruin_probability": ruin_count / n_paths,
        "double_probability": sum(1 for r in results if r >= starting_capital * 2) / n_paths,
    }

Output:

Monte Carlo Simulation (1,000 paths × N trades)
─────────────────────────────────────────────
Structure: WR=60%, RR=1.0, Risk=1.1%/trade
Starting Capital: $10,000

Median Terminal Equity:  $XX,XXX
5th Percentile:          $X,XXX
95th Percentile:         $XX,XXX
Max Drawdown (median):   XX.X%
P(Ruin):                 X.X%
P(Double):               XX.X%
─────────────────────────────────────────────
Verdict: [PASS/FAIL] — structure is [robust/fragile]

4. Portfolio Rebalance

Evaluates current allocation weights vs initial target weights.
Identifies momentum drift.
Outputs specific buy/sell orders to restore Kelly/Structural parity.

Reference Protocols

Protocol 367: High Win-Rate Supremacy
Protocol 368: Five Levers
Protocol 46: Trading Methodology

View source ↗

File metadata

name: zenith-execution
description: "Unified trade execution suite: Half-Kelly sizing, stop-loss calculation, Monte Carlo simulation, and portfolio rebalancing. Absorbs: kelly-mandate, stop-loss-calc, monte-carlo-sim, portfolio-rebalancer."
argument-hint: "setup | sizing | simulate | rebalance | optimize <ticker>"
allowed-tools:
  - Read
  - Bash
  - WebFetch
auto-invoke: true
model: default
context_trigger: "position sizing, Kelly, stop loss, Monte Carlo, simulate, rebalance, trade execution, portfolio optimization"

View original text

---
name: zenith-execution
description: "Unified trade execution suite: Half-Kelly sizing, stop-loss calculation, Monte Carlo simulation, and portfolio rebalancing. Absorbs: kelly-mandate, stop-loss-calc, monte-carlo-sim, portfolio-rebalancer."
argument-hint: "setup | sizing | simulate | rebalance | optimize <ticker>"
allowed-tools:
  - Read
  - Bash
  - WebFetch
auto-invoke: true
model: default
context_trigger: "position sizing, Kelly, stop loss, Monte Carlo, simulate, rebalance, trade execution, portfolio optimization"
---

# ZenithFX Execution Suite (Expanded)

> **Absorbs**: `kelly-mandate`, `stop-loss-calc`, `monte-carlo-sim`, `portfolio-rebalancer`

Unified quantitative execution skill for High Win-Rate trading systems (Protocol 367).

## Triggers

"zenith", "trade setup", "position size", "stop loss", "kelly criterion", "how much to risk", "invalidation point", "simulate", "monte carlo", "rebalance", "portfolio allocation"

## Sub-Commands

### 1. Position Sizing (Half-Kelly)

1. Demands Win Rate, Reward:Risk, and Total Capital.
2. Computes Full Kelly (theoretical optimum).
3. Halves it (Half-Kelly) for psychological variance and execution error.
4. Hard caps at 10% regardless of edge.

### 2. Stop-Loss (Structural Invalidation)

1. Identifies the price where the trade premise is demonstrably false.
2. Calculates distance between Entry and Invalidation.
3. Fits pre-determined Capital Risk % into that distance → Position Size.

**Rule**: A Stop Loss is a *structural invalidation point*, not an arbitrary budget allowance.

### 3. Monte Carlo Simulation

Simulates N independent trades through a given structure.

**Inputs**: Win Rate (%), Risk:Reward, Risk per trade (%), Number of trades (N), Starting capital.

```python
import random

def monte_carlo(wr, rr, risk_pct, n_trades, starting_capital, n_paths=1000):
    results = []
    ruin_count = 0
    max_drawdowns = []
    for _ in range(n_paths):
        equity = starting_capital
        peak = equity
        max_dd = 0
        for _ in range(n_trades):
            if random.random() < wr:
                equity += equity * risk_pct * rr
            else:
                equity -= equity * risk_pct
            peak = max(peak, equity)
            dd = (peak - equity) / peak
            max_dd = max(max_dd, dd)
            if equity <= starting_capital * 0.2:
                ruin_count += 1
                break
        results.append(equity)
        max_drawdowns.append(max_dd)
    results.sort()
    return {
        "median": results[len(results)//2],
        "p5": results[int(len(results)*0.05)],
        "p95": results[int(len(results)*0.95)],
        "max_dd_median": sorted(max_drawdowns)[len(max_drawdowns)//2],
        "ruin_probability": ruin_count / n_paths,
        "double_probability": sum(1 for r in results if r >= starting_capital * 2) / n_paths,
    }
```

**Output**:

```
Monte Carlo Simulation (1,000 paths × N trades)
─────────────────────────────────────────────
Structure: WR=60%, RR=1.0, Risk=1.1%/trade
Starting Capital: $10,000

Median Terminal Equity:  $XX,XXX
5th Percentile:          $X,XXX
95th Percentile:         $XX,XXX
Max Drawdown (median):   XX.X%
P(Ruin):                 X.X%
P(Double):               XX.X%
─────────────────────────────────────────────
Verdict: [PASS/FAIL] — structure is [robust/fragile]
```

### 4. Portfolio Rebalance

1. Evaluates current allocation weights vs initial target weights.
2. Identifies momentum drift.
3. Outputs specific buy/sell orders to restore Kelly/Structural parity.

## Reference Protocols

- Protocol 367: High Win-Rate Supremacy
- Protocol 368: Five Levers
- Protocol 46: Trading Methodology

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Review before install: Avoid automatic install

License: MIT

Financial research output is not financial advice; require human review before any live investment decision
Potential broker, wallet, exchange, or real-money execution surface; sandbox and explicit approval are required
AI review approval is missing
Financial research output is not financial advice; require human review before any live investment decision.
This skill may touch real-money trading, broker, wallet, or exchange operations; use only in a sandbox with explicit approval.
Quality score needs review
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Source & usage notes

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Source repository: winstonkoh87/Athena-Public
License: MIT
Version: Unknown
Last GitHub push: Sep 30, 2026
Registry updated: Oct 1, 2026
Instruction path: examples/skills/decision/zenith-execution/SKILL.md @ 38fbb0ed6abe

Version reported in registry metadata; check source releases before relying on it.

Quality

69/100

Promising

Trust

70/100

Sandbox only

Audit

80/100

Risky

Open full audit View eval report

Financial research output is not financial advice; require human review before any live investment decision
Potential broker, wallet, exchange, or real-money execution surface; sandbox and explicit approval are required
AI review approval is missing
Financial research output is not financial advice; require human review before any live investment decision.
This skill may touch real-money trading, broker, wallet, or exchange operations; use only in a sandbox with explicit approval.
Quality score needs review
Review status: AI review approval is missing

Verified installs: —
Outcomes: —

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More details

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winstonkoh87

Registry indexed

zenith-execution

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Price unconfirmed★ 592 GitHub starsRegistry updated · Oct 1, 2026agent-skill

Overview

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ZenithFX Execution Suite (Expanded)

Absorbs: kelly-mandate, stop-loss-calc, monte-carlo-sim, portfolio-rebalancer

Unified quantitative execution skill for High Win-Rate trading systems (Protocol 367).

Triggers

"zenith", "trade setup", "position size", "stop loss", "kelly criterion", "how much to risk", "invalidation point", "simulate", "monte carlo", "rebalance", "portfolio allocation"

Sub-Commands

1. Position Sizing (Half-Kelly)

Demands Win Rate, Reward:Risk, and Total Capital.
Computes Full Kelly (theoretical optimum).
Halves it (Half-Kelly) for psychological variance and execution error.
Hard caps at 10% regardless of edge.

2. Stop-Loss (Structural Invalidation)

Identifies the price where the trade premise is demonstrably false.
Calculates distance between Entry and Invalidation.
Fits pre-determined Capital Risk % into that distance → Position Size.

Rule: A Stop Loss is a structural invalidation point, not an arbitrary budget allowance.

3. Monte Carlo Simulation

Simulates N independent trades through a given structure.

Inputs: Win Rate (%), Risk:Reward, Risk per trade (%), Number of trades (N), Starting capital.

import random

def monte_carlo(wr, rr, risk_pct, n_trades, starting_capital, n_paths=1000):
    results = []
    ruin_count = 0
    max_drawdowns = []
    for _ in range(n_paths):
        equity = starting_capital
        peak = equity
        max_dd = 0
        for _ in range(n_trades):
            if random.random() < wr:
                equity += equity * risk_pct * rr
            else:
                equity -= equity * risk_pct
            peak = max(peak, equity)
            dd = (peak - equity) / peak
            max_dd = max(max_dd, dd)
            if equity <= starting_capital * 0.2:
                ruin_count += 1
                break
        results.append(equity)
        max_drawdowns.append(max_dd)
    results.sort()
    return {
        "median": results[len(results)//2],
        "p5": results[int(len(results)*0.05)],
        "p95": results[int(len(results)*0.95)],
        "max_dd_median": sorted(max_drawdowns)[len(max_drawdowns)//2],
        "ruin_probability": ruin_count / n_paths,
        "double_probability": sum(1 for r in results if r >= starting_capital * 2) / n_paths,
    }

Output:

Monte Carlo Simulation (1,000 paths × N trades)
─────────────────────────────────────────────
Structure: WR=60%, RR=1.0, Risk=1.1%/trade
Starting Capital: $10,000

Median Terminal Equity:  $XX,XXX
5th Percentile:          $X,XXX
95th Percentile:         $XX,XXX
Max Drawdown (median):   XX.X%
P(Ruin):                 X.X%
P(Double):               XX.X%
─────────────────────────────────────────────
Verdict: [PASS/FAIL] — structure is [robust/fragile]

4. Portfolio Rebalance

Evaluates current allocation weights vs initial target weights.
Identifies momentum drift.
Outputs specific buy/sell orders to restore Kelly/Structural parity.

Reference Protocols

Protocol 367: High Win-Rate Supremacy
Protocol 368: Five Levers
Protocol 46: Trading Methodology

View source ↗

File metadata

name: zenith-execution
description: "Unified trade execution suite: Half-Kelly sizing, stop-loss calculation, Monte Carlo simulation, and portfolio rebalancing. Absorbs: kelly-mandate, stop-loss-calc, monte-carlo-sim, portfolio-rebalancer."
argument-hint: "setup | sizing | simulate | rebalance | optimize <ticker>"
allowed-tools:
  - Read
  - Bash
  - WebFetch
auto-invoke: true
model: default
context_trigger: "position sizing, Kelly, stop loss, Monte Carlo, simulate, rebalance, trade execution, portfolio optimization"

View original text

---
name: zenith-execution
description: "Unified trade execution suite: Half-Kelly sizing, stop-loss calculation, Monte Carlo simulation, and portfolio rebalancing. Absorbs: kelly-mandate, stop-loss-calc, monte-carlo-sim, portfolio-rebalancer."
argument-hint: "setup | sizing | simulate | rebalance | optimize <ticker>"
allowed-tools:
  - Read
  - Bash
  - WebFetch
auto-invoke: true
model: default
context_trigger: "position sizing, Kelly, stop loss, Monte Carlo, simulate, rebalance, trade execution, portfolio optimization"
---

# ZenithFX Execution Suite (Expanded)

> **Absorbs**: `kelly-mandate`, `stop-loss-calc`, `monte-carlo-sim`, `portfolio-rebalancer`

Unified quantitative execution skill for High Win-Rate trading systems (Protocol 367).

## Triggers

"zenith", "trade setup", "position size", "stop loss", "kelly criterion", "how much to risk", "invalidation point", "simulate", "monte carlo", "rebalance", "portfolio allocation"

## Sub-Commands

### 1. Position Sizing (Half-Kelly)

1. Demands Win Rate, Reward:Risk, and Total Capital.
2. Computes Full Kelly (theoretical optimum).
3. Halves it (Half-Kelly) for psychological variance and execution error.
4. Hard caps at 10% regardless of edge.

### 2. Stop-Loss (Structural Invalidation)

1. Identifies the price where the trade premise is demonstrably false.
2. Calculates distance between Entry and Invalidation.
3. Fits pre-determined Capital Risk % into that distance → Position Size.

**Rule**: A Stop Loss is a *structural invalidation point*, not an arbitrary budget allowance.

### 3. Monte Carlo Simulation

Simulates N independent trades through a given structure.

**Inputs**: Win Rate (%), Risk:Reward, Risk per trade (%), Number of trades (N), Starting capital.

```python
import random

def monte_carlo(wr, rr, risk_pct, n_trades, starting_capital, n_paths=1000):
    results = []
    ruin_count = 0
    max_drawdowns = []
    for _ in range(n_paths):
        equity = starting_capital
        peak = equity
        max_dd = 0
        for _ in range(n_trades):
            if random.random() < wr:
                equity += equity * risk_pct * rr
            else:
                equity -= equity * risk_pct
            peak = max(peak, equity)
            dd = (peak - equity) / peak
            max_dd = max(max_dd, dd)
            if equity <= starting_capital * 0.2:
                ruin_count += 1
                break
        results.append(equity)
        max_drawdowns.append(max_dd)
    results.sort()
    return {
        "median": results[len(results)//2],
        "p5": results[int(len(results)*0.05)],
        "p95": results[int(len(results)*0.95)],
        "max_dd_median": sorted(max_drawdowns)[len(max_drawdowns)//2],
        "ruin_probability": ruin_count / n_paths,
        "double_probability": sum(1 for r in results if r >= starting_capital * 2) / n_paths,
    }
```

**Output**:

```
Monte Carlo Simulation (1,000 paths × N trades)
─────────────────────────────────────────────
Structure: WR=60%, RR=1.0, Risk=1.1%/trade
Starting Capital: $10,000

Median Terminal Equity:  $XX,XXX
5th Percentile:          $X,XXX
95th Percentile:         $XX,XXX
Max Drawdown (median):   XX.X%
P(Ruin):                 X.X%
P(Double):               XX.X%
─────────────────────────────────────────────
Verdict: [PASS/FAIL] — structure is [robust/fragile]
```

### 4. Portfolio Rebalance

1. Evaluates current allocation weights vs initial target weights.
2. Identifies momentum drift.
3. Outputs specific buy/sell orders to restore Kelly/Structural parity.

## Reference Protocols

- Protocol 367: High Win-Rate Supremacy
- Protocol 368: Five Levers
- Protocol 46: Trading Methodology

Review the source

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License: MIT
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Skill source recorded

Skill instructions are recorded. This is not a runtime test, safety guarantee or compatibility certification.

Review before install: Avoid automatic install

License: MIT

Financial research output is not financial advice; require human review before any live investment decision
Potential broker, wallet, exchange, or real-money execution surface; sandbox and explicit approval are required
AI review approval is missing
Financial research output is not financial advice; require human review before any live investment decision.
This skill may touch real-money trading, broker, wallet, or exchange operations; use only in a sandbox with explicit approval.
Quality score needs review
Review status: AI review approval is missing

Open full audit

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Start with one small task

1Read the source. Confirm the input, expected output, dependencies and permissions.
2Ask your agent for a plan. Approve setup and any costs before running a small isolated test.
3Check the output and changed files. Report only what actually ran; keep the source revision for reproduction.

Check the source for dependencies, API keys and third-party costs. A public repository does not mean every service is free.

Source & usage notes

IndexedStatic Checked

Repository metadata and review signals are advisory. Popularity, source discovery and successful execution are different facts.

Source repository: winstonkoh87/Athena-Public
License: MIT
Version: Unknown
Last GitHub push: Sep 30, 2026
Registry updated: Oct 1, 2026
Instruction path: examples/skills/decision/zenith-execution/SKILL.md @ 38fbb0ed6abe

Version reported in registry metadata; check source releases before relying on it.

Quality

69/100

Promising

Trust

70/100

Sandbox only

Audit

80/100

Risky

Open full audit View eval report

Financial research output is not financial advice; require human review before any live investment decision
Potential broker, wallet, exchange, or real-money execution surface; sandbox and explicit approval are required
AI review approval is missing
Financial research output is not financial advice; require human review before any live investment decision.
This skill may touch real-money trading, broker, wallet, or exchange operations; use only in a sandbox with explicit approval.
Quality score needs review
Review status: AI review approval is missing

Verified installs: —
Outcomes: —

Copies are not installs. Installation counts require a reported successful installation; they are not a blanket quality guarantee.

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More details

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    "web": "https://www.openagentskill.com/skills/winstonkoh87-zenith-execution",
    "api": "https://www.openagentskill.com/api/agent/skills/winstonkoh87-zenith-execution",
    "audit": "https://www.openagentskill.com/skills/winstonkoh87-zenith-execution/audit",
    "eval": "https://www.openagentskill.com/api/agent/evals?slug=winstonkoh87-zenith-execution&task=Use%20zenith-execution%20in%20an%20agent%20workflow&max_risk=medium",
    "resolve": "https://www.openagentskill.com/api/agent/resolve?task=Use%20zenith-execution%20in%20an%20agent%20workflow&agent=codex&max_risk=medium",
    "receipt": "https://www.openagentskill.com/api/agent/receipt?task=Use%20zenith-execution%20in%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text",
    "install": "https://www.openagentskill.com/api/skills/winstonkoh87-zenith-execution/install",
    "manifest": "https://www.openagentskill.com/api/registry/manifest/winstonkoh87-zenith-execution"
  }
}

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Creator: winstonkoh87
Source: winstonkoh87/Athena-Public
Indexed by: OpenAgentSkill community index

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Overview

ZenithFX Execution Suite (Expanded)

Triggers

Sub-Commands

1. Position Sizing (Half-Kelly)

2. Stop-Loss (Structural Invalidation)

3. Monte Carlo Simulation

4. Portfolio Rebalance

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Price & running costs

Start with one small task

Source & usage notes

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Overview

ZenithFX Execution Suite (Expanded)

Triggers

Sub-Commands

1. Position Sizing (Half-Kelly)

2. Stop-Loss (Structural Invalidation)

3. Monte Carlo Simulation

4. Portfolio Rebalance

Reference Protocols

Review the source

Price & running costs

Start with one small task

Source & usage notes

Agent access

Related skills

For the creator

Registry indexed

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Community signal