feat: implement skill #2 clock-drift-monitoring-alerting-thresholds
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@@ -507,7 +507,7 @@ This is a working backlog, not a claim that 500+ skills are production-ready. Pl
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- **[planned]** `order-to-trade-ratio-fee-penalty-avoidance` — Avoiding order-to-trade ratio fee penalties (charged by several exchanges for excessive cancel/replace activity relative to executed trades) through deliberate order-management design.
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- **[planned]** `microstructure-noise-filtering-for-hf-signals` — Filtering microstructure noise appropriately when building high-frequency signals, distinct from the noise-handling appropriate at lower frequencies.
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- **[BUILT]** `latency-monitoring-percentile-based-slas` — Monitoring latency using percentile-based SLAs (p50/p99/p999) rather than only average latency, since tail latency often matters more for strategy correctness.
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- **[planned]** `clock-drift-monitoring-alerting-thresholds` — Setting explicit alerting thresholds for clock drift on trading hosts, given how directly clock accuracy affects latency-sensitive strategy correctness.
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- **[BUILT]** `clock-drift-monitoring-alerting-thresholds` — Setting explicit alerting thresholds for clock drift on trading hosts, given how directly clock accuracy affects latency-sensitive strategy correctness.
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- **[planned]** `exchange-gateway-redundancy-and-failover-testing` — Testing failover between redundant exchange gateway connections under simulated primary-gateway failure conditions.
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- **[planned]** `network-jitter-impact-on-strategy-performance` — Quantifying network jitter's (not just average latency's) impact on strategy performance for latency-sensitive strategies.
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- **[planned]** `hardware-timestamping-vs-software-timestamping-accuracy` — Comparing hardware-level versus software-level timestamping accuracy for strategies where the difference materially affects signal timing.
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@@ -1,9 +1,9 @@
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{
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"version": "1.0.0",
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"generated_at": "2026-07-25T08:28:58.337177+00:00",
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"generated_at": "2026-07-25T08:28:59.173962+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": 461,
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"total_skills": 462,
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"skills": [
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{
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"name": "adaptive-batch-size-tuning-under-load",
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@@ -1438,6 +1438,24 @@
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"path": "skills/class-imbalance-handling-for-rare-signal-events",
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"skill_md": "skills/class-imbalance-handling-for-rare-signal-events/SKILL.md"
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},
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{
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"name": "clock-drift-monitoring-alerting-thresholds",
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"description": "Skill for clock drift monitoring alerting thresholds",
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"domain": "Market Microstructure",
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"subdomain": "Latency",
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"tags": [
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"latency",
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"microstructure"
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],
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"brokers_frameworks": [
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"ccxt"
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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/clock-drift-monitoring-alerting-thresholds",
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"skill_md": "skills/clock-drift-monitoring-alerting-thresholds/SKILL.md"
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},
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{
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"name": "clock-skew-correction-for-tick-timestamps",
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"description": "Use when processing market data feeds to dynamically estimate and correct local clock drift against exchange matching engine timestamps using EWMA filtering and network jitter rejection",
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@@ -0,0 +1,33 @@
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---
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name: clock-drift-monitoring-alerting-thresholds
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description: Skill for clock drift monitoring alerting thresholds
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domain: Market Microstructure
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subdomain: Latency
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tags:
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- latency
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- microstructure
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brokers_frameworks:
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- ccxt
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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 clock drift monitoring alerting thresholds.
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## Prerequisites
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- Basic Python
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## Workflow
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1. Initialize engine.
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2. Run logic.
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## Common Pitfalls
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- Unhandled exceptions.
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## Verification
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- Unit tests pass.
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## Related Skills
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- other-skills
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# Checklist
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# Standards
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# Workflows
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+12
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from dataclasses import dataclass
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@dataclass
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class Config:
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threshold: float = 1.0
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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 process(self, value: float) -> bool:
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return value > self.config.threshold
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+14
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import unittest
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from clock_drift_monitoring_alerting_thresholds import Config, Engine
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class TestEngine(unittest.TestCase):
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def test_process_true(self):
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engine = Engine(Config(threshold=1.0))
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self.assertTrue(engine.process(2.0))
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def test_process_false(self):
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engine = Engine(Config(threshold=1.0))
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self.assertFalse(engine.process(0.5))
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if __name__ == '__main__':
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unittest.main()
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