Skill UI

Analyzes options chain data by separating real calls and puts from lottery-like speculative contracts to produce more reliable put/call sentiment, anomaly detection, and expiry breakdowns for watchlists, sectors, and event-driven names.

This meta-skill automates the entire process of transforming raw Excel data into structured business insights. It reads the raw data, performs advanced trend and anomaly analysis, writes the resulting findings to a dedicated 'Insights' sheet, and persists key performance indicators (KPIs) to long-term memory. Ideal for comprehensive business reviews and data-driven decision-making.

This tool performs robust outlier detection on individual session spending. Utilizing Median and Median Absolute Deviation (MAD), it calculates a modified z-score, making it highly resistant to extreme values, unlike mean+sigma methods. It specifically identifies which singular sessions are anomalous, making it crucial for cost monitoring, auditing, and integrating into CI/CD pipelines to prevent unexpected resource overruns.

This composite CI gate runs four critical cost monitoring checks—budget, burn, anomaly, and projection—in parallel. It surfaces a single, combined health status by taking the maximum exit code. This tool is an operational entry point for integrating comprehensive resource spending alerts directly into CI/CD pipelines, ensuring that resource usage remains within defined boundaries and predicts potential budget overruns.

This tool provides a granular, per-message cost breakdown within a single conversation session. It serves as a deep-dive utility following an anomaly detection, allowing operators to pinpoint exactly which messages incurred the highest costs. It reveals critical cost components like output tokens, cache writes, and model escalations, helping users understand the true resource consumption beyond simple token counts.

This utility detects and classifies various anomalies (such as spikes, flatlines, drift, or pattern breaks) within telemetry data streamed from IoT devices. It utilizes Z-score anomaly detection to provide actionable insights. This is crucial for investigating unusual device metrics, ensuring system health before deploying major firmware updates (canary advancement), or triaging fleet-wide operational alerts.

This tool orchestrates the entire firmware rollout lifecycle across large device fleets. It supports controlled, gradual deployment strategies, including canary testing and anomaly-gated advancement. Users can deploy new versions, check real-time status, execute rollbacks, or list all ongoing rollout campaigns, ensuring stable and reliable updates.

A comprehensive tool for aggregating and displaying system metrics (counters, gauges, histograms) from the observability namespace. It computes baselines and flags anomalies by detecting deviations exceeding standard deviations, providing a clear snapshot of system health, error rates, and performance degradation trends.

This tool generates sophisticated trading signals by leveraging an advanced anomaly detection engine. It scans financial assets for various market anomalies—such as spikes, drifts, and oscillations—and classifies them. It then integrates neural network prediction and searches historical pattern databases to output highly ranked, actionable trading signals, complete with confidence scores and target parameters.

A comprehensive tool to scan all connected digital marketing platforms (e.g., Google Ads, Meta, TikTok) for statistically significant deviations from established performance baselines. It detects performance drops (traffic, conversions, ROAS) or unexpected growth opportunities, classifying anomalies by severity (Critical, Warning, Info) and providing probable root causes and immediate action plans. Essential for proactive campaign management and cost control.

This tool guides researchers to elevate a simple research topic into a profound theoretical puzzle suitable for top-tier organizational science journals like ASQ. It helps identify the core anomaly, the sociological tension, and the surprising insight required to challenge existing theory and generate new, generative research avenues.

This guide provides a structured methodology for academic writing, enabling researchers to move beyond stating a mere 'lack of research.' It teaches users how to rigorously pinpoint the theoretical gap—such as an unaddressed mechanism, an inexplicable anomaly, or an undefined boundary condition—that existing theories fail to explain. Essential for strengthening the theoretical depth and academic impact of scholarly papers.