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Read-only: calculates refund rate by product, collection, or period — identifies quality and listing issues.
Analise de mercado imobiliario para leiloes. Liquidez, desagio tipico, ROI, estrategias de saida (flip/reforma/renda), Selic 2025 e benchmark CDI/FII.
Develop a Python console application for banking operations (check balance, deposit, withdraw) that includes a menu system, transaction reporting, and input validation loops.
Candlestick pattern recognition engine, pure pandas vectorized implementation of 15 classic candlestick patterns (5 single-candle + 5 double-candle + 4 triple-candle + 1 trend confirmation), generating a composite signal from bullish/bearish pattern scores.
Analyze revenue by cohort. TRIGGERS - Use when user needs help with cohort-revenue-analysis related tasks.
Conduct cost-benefit analyses for decision making. TRIGGERS - Use when user needs help with cost-benefit-analysis related tasks.
Create data classification schemes with handling procedures. TRIGGERS - Use when user needs help with data-classification related tasks.
Design financial analytics dashboards. TRIGGERS - Use when user needs help with financial-analytics-plan related tasks.
Use when tasks involve creating, editing, analyzing, or formatting spreadsheets (`.xlsx`, `.csv`, `.tsv`) with formula-aware workflows, cached recalculation, and visual review.
Read-only: Compute refund rate by product, category, or period from order and refund data.
Read-only: Break down net revenue contribution by WooCommerce product category for a specified period.
Use when reviewing, scoring, or auditing third-party SaaS / vendor relationships — running a vendor scorecard, tracking SLA compliance, classifying third-party risk, preparing a tier-1 vendor review, or auditing the SaaS portfolio. Triggers on "vendor SLA", "vendor scorecard", "third-party risk",...
This skill should be used when the user asks about "key startup metrics", "SaaS metrics", "CAC and LTV", "unit economics", "burn multiple", "rule of 40", "marketplace metrics", or requests guidance on tracking and optimizing business performance metrics.
Comprehensive toolkit for creating, analyzing, and visualizing complex networks and graphs in Python. Use when working with network/graph data structures, analyzing relationships between entities, computing graph algorithms (shortest paths, centrality, clustering), detecting communities, generati...
Query PubChem via PUG-REST API/PubChemPy (110M+ compounds). Search by name/CID/SMILES, retrieve properties, similarity/substructure searches, bioactivity, for cheminformatics.
Query STRING API for protein-protein interactions (59M proteins, 20B interactions). Network analysis, GO/KEGG enrichment, interaction discovery, 5000+ species, for systems biology.
UMAP dimensionality reduction. Fast nonlinear manifold learning for 2D/3D visualization, clustering preprocessing (HDBSCAN), supervised/parametric UMAP, for high-dimensional data.
Use Firecrawl to search, scrape, crawl, and interact with the web through an API built for AI agents. It returns clean markdown, structured JSON, screenshots, and crawl results that plug neatly into research, extraction, and retrieval workflows.
Analyze user research data to uncover insights, identify patterns, and inform design decisions. Synthesize qualitative and quantitative research into actionable recommendations.
Use this skill when the user requests to generate, create, or write professional research reports including but not limited to market analysis, consumer insights, brand analysis, financial analysis, industry research, competitive intelligence, investment due diligence, or any consulting-grade ana...
Conducts thorough landscape research, competitive analysis, best practices evaluation, and evidence-based recommendations. Expert in market research and trend analysis.
Automated content similarity and grouping analysis. Groups related documents by topic, purpose, or content similarity.
This skill should be used when the user asks to "calculate TAM",
Neo4j graph database with Cypher query language. Use for graph-based data.
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