Skill UI

Build a production-ready, AI-powered data collection agent for any public source (job boards, prices, news, etc.). This agent automatically scrapes data, enriches it using free LLMs (like Gemini Flash), and stores the results in databases such as Notion, Sheets, or Supabase. It runs on a free schedule using GitHub Actions and learns from user feedback, making it ideal for continuous data monitoring and tracking.

A comprehensive methodology for accelerating large-scale data ingestion, ETL processes, backfilling, and data warehouse loading. It guides users in identifying and optimizing bottlenecks—such as source extraction, network transfer, and loading speed—while strictly ensuring data correctness and maintaining clear accounting checkpoints throughout the pipeline.

This tool detects and classifies anomalies (such as spikes, drift, flatlines, or pattern breaks) in the telemetry data streamed from Cognitum Seed IoT devices. It utilizes Z-score analysis to quantify the deviation from normal operational metrics. Use this when investigating unexpected device behavior, validating stability before firmware advancements, or triaging large-scale fleet health alerts.

A read-only tool designed to compare prediction-market baskets or themes against the user's existing knowledge base, portfolio notes, research memos, or financial context. It performs gap analysis, flagging potential conflicts, stale assumptions, and areas of missing research. This skill provides structured insights into fit and exposure without offering any investment or trading advice.

This skill provides comprehensive, read-only market intelligence for prediction markets. It helps users research market events, compare different venues (like Polymarket, Kalshi), analyze liquidity, and understand underlying assets. It generates source-grounded briefings, emphasizing context and data quality, and strictly avoids providing investment or trading advice.

This powerful tool scans ingested OHLCV market data to detect and classify known candlestick patterns, such as Doji, Hammer, Engulfing, and Head & Shoulders. It analyzes single, multi-, and complex candle sequences, assigning a pattern name, type (reversal/continuation), direction, and a reliability score (0.0-1.0). Ideal for technical traders needing structured pattern identification for advanced market analysis.

This tool aggregates various system metrics—including counters, gauges, and histograms—from the observability namespace. It calculates baselines, flags significant deviations (anomalies) based on statistical standards, and provides a comprehensive system health report. Use it to get a detailed snapshot of system performance, monitor for degradation, and ensure overall system stability.

This guide provides a comprehensive workflow for searching and retrieving biomedical literature from PubMed and NCBI. It covers advanced query construction using MeSH terms and specific field tags, advanced filtering (date, publication type), and a repeatable programmatic workflow using NCBI E-utilities (esearch, efetch). Essential for researchers conducting systematic reviews and literature monitoring.

This skill provides a structured framework for designing and implementing composable recommendation, ranking, and feed pipelines. It models the industry-standard six-stage pattern: Source, Hydrator, Filter, Scorer, Selector, and SideEffect. Use it for any system that selects "the top K items for a (user, context)", such as social feeds, ad ranking, RAG rerankers, or content recommendation engines, ensuring a robust and scalable architecture.

This is an advanced, structured workflow designed to conduct deep, multi-source investigations. It synthesizes current public evidence with user-provided context to generate highly structured reports. The workflow explicitly differentiates between verifiable facts, user-supplied evidence, logical inferences, and actionable recommendations, making it ideal for complex comparative analysis or continuous monitoring tasks.

This tool synthesizes deep, accumulated research findings stored in memory into structured, actionable reports. It systematically grades evidence quality (High, Medium, Low), identifies and resolves conflicting claims, and generates comprehensive outputs including an executive summary, ranked key findings, limitations, and concrete recommendations. Ideal for transforming raw research data into strategic insights.

An advanced tool for network intelligence that calculates weighted graph scores to map the optimal path to a target. It identifies potential introducers, measures 'bridge value' across connections, and helps determine whether a connection requires a warm introduction or direct outreach on platforms like X and LinkedIn. Ideal for users needing the raw ranking methodology.