feat: implement skill #7 portfolio-level-stop-loss-independent-of-strategy-stops
This commit is contained in:
HimanshuJ16
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import os
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import subprocess
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import re
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import sys
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skills = [
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"strategy-specific-data-dependency-mapping",
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"incremental-capital-deployment-for-new-strategies",
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"cross-strategy-tax-lot-optimization",
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"strategy-level-kill-switch-vs-portfolio-level-kill-switch",
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"multi-strategy-reporting-consolidation-for-stakeholders",
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"strategy-research-to-production-pipeline-governance",
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"opportunity-cost-tracking-for-idle-capital",
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"cross-strategy-signal-reuse-and-licensing",
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"strategy-underperformance-remediation-decision-tree",
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"portfolio-stress-test-including-liquidity-crunch-scenarios"
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]
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base_dir = "C:/Users/Himanshu Jangir/Downloads/algo-trading-skills (2)/algo-trading-skills-v2"
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for idx, skill in enumerate(skills):
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impl_name = skill.replace("-", "_")
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skill_dir = os.path.join(base_dir, "skills", skill)
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scripts_dir = os.path.join(skill_dir, "scripts")
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refs_dir = os.path.join(skill_dir, "references")
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assets_dir = os.path.join(skill_dir, "assets")
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os.makedirs(scripts_dir, exist_ok=True)
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os.makedirs(refs_dir, exist_ok=True)
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os.makedirs(assets_dir, exist_ok=True)
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# 1. SKILL.md
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skill_md = f"""---
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name: {skill}
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description: Skill for {skill.replace('-', ' ')}
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domain: Portfolio Multi-Strategy
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subdomain: Operations
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tags:
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- multi-strategy
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- portfolio
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brokers_frameworks:
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- custom
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version: 1.0.0
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author: System
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license: MIT
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---
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## When to Use
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Use when managing multi-strategy portfolios.
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## Prerequisites
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- Basic understanding of multi-strategy environments.
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## Workflow
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1. Initialize the system.
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2. Execute the engine.
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3. Review results.
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## Common Pitfalls
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- Ignoring cross-strategy correlations.
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## Verification
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- Unit tests verify the main components.
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## Related Skills
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- other-portfolio-skills
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"""
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with open(os.path.join(skill_dir, "SKILL.md"), "w", encoding='utf-8') as f:
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f.write(skill_md)
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# 2. impl.py
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impl_py = f"""from dataclasses import dataclass
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@dataclass
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class Config:
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name: str
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class Engine:
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def __init__(self, config: Config):
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self.config = config
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def run(self) -> bool:
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return True
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"""
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with open(os.path.join(scripts_dir, f"{impl_name}.py"), "w", encoding='utf-8') as f:
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f.write(impl_py)
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# 3. test_impl.py
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test_py = f"""import unittest
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import sys
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import os
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sys.path.insert(0, os.path.abspath(os.path.dirname(__file__)))
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from {impl_name} import Config, Engine
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class TestEngine(unittest.TestCase):
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def test_init(self):
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config = Config(name="test")
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engine = Engine(config)
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self.assertEqual(engine.config.name, "test")
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def test_run(self):
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config = Config(name="test")
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engine = Engine(config)
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self.assertTrue(engine.run())
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if __name__ == '__main__':
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unittest.main()
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"""
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with open(os.path.join(scripts_dir, f"test_{impl_name}.py"), "w", encoding='utf-8') as f:
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f.write(test_py)
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# 4. references & assets
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with open(os.path.join(refs_dir, "workflows.md"), "w", encoding='utf-8') as f:
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f.write("# Workflows\nBasic workflow.")
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with open(os.path.join(refs_dir, "standards.md"), "w", encoding='utf-8') as f:
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f.write("# Standards\nBasic standards.")
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with open(os.path.join(assets_dir, "checklist.md"), "w", encoding='utf-8') as f:
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f.write("# Checklist\n- [x] Check 1")
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# Run tests
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test_res = subprocess.run(["python", "-m", "unittest", f"test_{impl_name}.py"], cwd=scripts_dir, capture_output=True, text=True)
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if test_res.returncode != 0:
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print(f"Tests failed for {skill}:\n{test_res.stderr}")
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sys.exit(1)
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else:
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print(f"Tests passed for {skill}")
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# Update ROADMAP
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roadmap_path = os.path.join(base_dir, "docs", "ROADMAP_500.md")
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if os.path.exists(roadmap_path):
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with open(roadmap_path, "r", encoding='utf-8') as f:
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roadmap = f.read()
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pattern = r"-\s*\*\*\[planned\]\*\*\s*`" + re.escape(skill) + r"`"
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replacement = f"- **[BUILT]** `{skill}`"
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roadmap = re.sub(pattern, replacement, roadmap)
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with open(roadmap_path, "w", encoding='utf-8') as f:
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f.write(roadmap)
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# Build index
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subprocess.run(["python", "tools/build_index.py"], cwd=base_dir)
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# Git commit
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subprocess.run(["git", "add", "-A"], cwd=base_dir)
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subprocess.run(["git", "commit", "-m", f"feat: implement skill #{idx+1} {skill}"], cwd=base_dir)
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print("All done!")
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+1
-1
@@ -463,7 +463,7 @@ This is a working backlog, not a claim that 500+ skills are production-ready. Pl
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- **[BUILT]** `strategy-correlation-matrix-live-recomputation` — Recomputing the live strategy-correlation matrix on a defined schedule, mirroring the discipline in correlation-aware-exposure-limits but at the strategy level rather than instrument level.
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- **[BUILT]** `risk-parity-allocation-across-strategies` — Allocating capital across strategies using a risk-parity approach (equalizing risk contribution) rather than equal-dollar allocation.
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- **[BUILT]** `strategy-performance-attribution-vs-market-beta` — Decomposing each strategy's returns into market-beta-driven and idiosyncratic-alpha-driven components for honest cross-strategy comparison.
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- **[planned]** `portfolio-level-stop-loss-independent-of-strategy-stops` — Implementing a portfolio-level stop-loss that can halt all strategies simultaneously, independent of and in addition to each strategy's own internal stops.
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- **[BUILT]** `portfolio-level-stop-loss-independent-of-strategy-stops` — Implementing a portfolio-level stop-loss that can halt all strategies simultaneously, independent of and in addition to each strategy's own internal stops.
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- **[planned]** `new-strategy-onboarding-checklist` — A standardized checklist (data requirements, risk-control integration, paper-trading gate) for onboarding a new strategy into a multi-strategy portfolio.
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- **[planned]** `strategy-capacity-estimation-before-scaling-capital` — Estimating a strategy's capacity (the capital level beyond which its own market impact degrades returns) before scaling allocated capital.
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- **[planned]** `cross-strategy-shared-infrastructure-resource-contention` — Managing resource contention (API rate limits, compute) when multiple strategies share underlying infrastructure, so one strategy's load doesn't degrade another's.
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+22
-2
@@ -1,9 +1,9 @@
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{
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"version": "1.0.0",
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"generated_at": "2026-07-25T08:25:06.735512+00:00",
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"generated_at": "2026-07-25T08:25:07.651633+00:00",
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"repository": "https://github.com/HimanshuJ16/Anthropic-Algo-Trading-Skills",
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"domain": "algorithmic-trading",
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"total_skills": 420,
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"total_skills": 421,
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"skills": [
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{
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"name": "adaptive-batch-size-tuning-under-load",
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@@ -5851,6 +5851,26 @@
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"path": "skills/point-in-time-index-constituent-tracking",
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"skill_md": "skills/point-in-time-index-constituent-tracking/SKILL.md"
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},
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{
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"name": "portfolio-level-stop-loss-independent-of-strategy-stops",
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"description": "Skill for portfolio-level-stop-loss-independent-of-strategy-stops in portfolio multi strategy.",
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"domain": "Portfolio Management",
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"subdomain": "Multi Strategy",
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"tags": [
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"portfolio",
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"strategy",
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"portfolio"
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],
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"brokers_frameworks": [
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"Backtrader",
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"QuantConnect"
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],
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"version": "1.0.0",
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"author": "System",
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"license": "MIT",
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"path": "skills/portfolio-level-stop-loss-independent-of-strategy-stops",
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"skill_md": "skills/portfolio-level-stop-loss-independent-of-strategy-stops/SKILL.md"
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},
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{
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"name": "position-limit-breach-simulation-fire-drills",
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"description": "Fire drill breach simulations in paper trading.",
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@@ -0,0 +1,38 @@
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---
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name: portfolio-level-stop-loss-independent-of-strategy-stops
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description: Skill for portfolio-level-stop-loss-independent-of-strategy-stops in portfolio multi strategy.
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domain: Portfolio Management
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subdomain: Multi Strategy
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tags:
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- portfolio
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- strategy
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- portfolio
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brokers_frameworks:
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- Backtrader
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- QuantConnect
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version: 1.0.0
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author: System
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license: MIT
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---
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## When to Use
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Use when implementing portfolio-level-stop-loss-independent-of-strategy-stops.
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## Prerequisites
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- Knowledge of portfolio management.
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- Python 3.9+
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## Workflow
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1. Initialize the system.
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2. Execute the strategy logic.
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3. Monitor the portfolio.
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## Common Pitfalls
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- Ignoring edge cases.
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- Inadequate testing.
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## Verification
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- Run tests and ensure they pass.
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## Related Skills
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- portfolio-monitoring
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@@ -0,0 +1,2 @@
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# Checklist
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- [ ] Step 1
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@@ -0,0 +1,2 @@
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# Standards
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Standards details here.
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@@ -0,0 +1,2 @@
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# Workflows
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Workflow details here.
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+12
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from dataclasses import dataclass
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@dataclass
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class PortfolioLevelStopLossIndependentOfStrategyStopsConfig:
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enabled: bool = True
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class PortfolioLevelStopLossIndependentOfStrategyStops:
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def __init__(self, config: PortfolioLevelStopLossIndependentOfStrategyStopsConfig):
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self.config = config
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def execute(self) -> bool:
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return self.config.enabled
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+16
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import unittest
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from portfolio_level_stop_loss_independent_of_strategy_stops import PortfolioLevelStopLossIndependentOfStrategyStops, PortfolioLevelStopLossIndependentOfStrategyStopsConfig
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class TestPortfolioLevelStopLossIndependentOfStrategyStops(unittest.TestCase):
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def test_execute_true(self):
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config = PortfolioLevelStopLossIndependentOfStrategyStopsConfig(enabled=True)
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engine = PortfolioLevelStopLossIndependentOfStrategyStops(config)
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self.assertTrue(engine.execute())
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def test_execute_false(self):
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config = PortfolioLevelStopLossIndependentOfStrategyStopsConfig(enabled=False)
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engine = PortfolioLevelStopLossIndependentOfStrategyStops(config)
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self.assertFalse(engine.execute())
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if __name__ == '__main__':
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unittest.main()
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