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Found 323 Skills
Exécute des requêtes SQL en lecture seule sur plusieurs bases de données PostgreSQL. À utiliser pour : (1) interroger des bases PostgreSQL, (2) explorer les schémas/tables, (3) exécuter des requêtes SELECT pour l'analyse de données, (4) vérifier le contenu des bases. Supporte plusieurs connexions avec descriptions pour une sélection automatique intelligente. Bloque toutes les opérations d'écriture (INSERT, UPDATE, DELETE, DROP, etc.) par sécurité.
Explore, interpret, and draw conclusions from football data. Use when the user wants to analyse match events, compare teams or players, understand tactical patterns, build visualisations, or needs guidance on what questions to ask of their data. Adapts to the user's experience level.
Run ClickHouse queries for analytics, metrics analysis, and event data exploration. Use when you need to query ClickHouse directly, analyze metrics, check event tracking data, or test query performance. Read-only by default.
Interpret medical lab/test reports (blood panels, urine, liver/kidney function, thyroid, tumor markers, coagulation, cardiac enzymes, hormones, etc.) uploaded as images, PDFs, or text. Trigger whenever the user uploads a lab report, medical test result, or clinical diagnostic sheet — or says things like "help me read this report", "what do these results mean", "化验单", "检验报告", "帮我看看这个报告", "blood test results", "lab results", "体检报告", "检查报告单", "血常规", "尿常规", "肝功能", "肾功能", "甲功", "凝血", "interpret my labs", "are these results normal", "这些指标正常吗". Also trigger when the user uploads ANY medical-looking document with tables of values, reference ranges, or clinical test names — even if they don't explicitly ask for interpretation. Do NOT trigger for symptom triage (use emergency-triage instead), drug interaction queries, or general medical Q&A without an actual report to interpret.
Count the Tokens consumed by the local Codex in recent time by task purpose dimension, and output a Chinese table including model and category proportions; output the Faster x2 status only when explicit session-level fields exist.
Generate a concise 4-5 page equity research earnings preview for a single company. Analyzes the most recent earnings transcript, competitor landscape, valuation, and recent news to produce a professional HTML report.
Guides the user through building composite score workflows when they ask about composite scores, indexes, multi-variable scores, ranking areas, site scoring, market potential, resilience indexes, risk indexes, weighted scores, PCA, or supervised/unsupervised scoring.
Research computing toolkit for optoelectronic information science and engineering, MATLAB/Octave, Python scientific analysis, signal processing, image processing, statistics, simulation, optimization, publication figures, sensor/time-series data, citation lookup, and common scientific libraries. Use when the user asks for MATLAB code, scientific Python, data analysis, plots, simulations, formulas, statistics, machine learning, optical/physical/materials computation, or reproducible research workflows.
Run nf-core bioinformatics pipelines (rnaseq, sarek, atacseq) on sequencing data. Use when analyzing RNA-seq, WGS/WES, or ATAC-seq data—either local FASTQs or public datasets from GEO/SRA. Triggers on nf-core, Nextflow, FASTQ analysis, variant calling, gene expression, differential expression, GEO reanalysis, GSE/GSM/SRR accessions, or samplesheet creation.
Screen US stocks using William O'Neil's CANSLIM growth stock methodology. Use when user requests CANSLIM stock screening, growth stock analysis, momentum stock identification, or wants to find stocks with strong earnings and price momentum following O'Neil's investment system.
Best practices for creating comprehensive Jupyter notebook data analyses with statistical rigor, outlier handling, and publication-quality visualizations
Expert in Python development with best practices across web, data science, and automation