developing-heart-local
Developing Heart Atlas notebooks converted to HTML (local)
发现 documentation data analysis 相关 Skills,比较来源仓库和用途,查看适合你工作流的技能说明。
Developing Heart Atlas notebooks converted to HTML (local)
MuData 多模态数据分析工具包 - 100%覆盖文档(API+教程+IO指南+核心功能)
SpatialData framework for handling spatial multi-modal and multi-scale data. Use this skill for questions about spatial omics data analysis, visualization, and the SpatialData Python ecosystem.
Comprehensive spreadsheet creation, editing, and analysis with support for formulas, formatting, data analysis, and visualization. When MiniMax-M2 needs to work with spreadsheets (.xlsx, .xlsm, .csv, .tsv, etc)...
Generate and execute Python code to analyze large log datasets, detect patterns, and extract actionable insights
Comprehensive spreadsheet work including creation, editing, and analysis of Excel files (.xlsx, .xlsm, .csv, .tsv). When Claude needs to work with spreadsheets for data analysis, financial modeling, or any Exce...
Write structured experiment sections (methods + results + discussion) for NQS + SQD projects in this repository, based on contents of results/ and figures/.
Database schemas, table specifications, and migration information. Use when working with database structure or queries.
Comprehensive validation of FTD analysis output files. Checks JSONL format, field completeness, score validity, and structural requirements for TALD scale evaluations.
Expert guidance on statistical analysis methodologies and Monte Carlo simulation for fantasy football. Use this skill when selecting regression approaches, designing simulations, performing variance analysis, o...
Create Jupyter notebooks for FF Analytics following project conventions. Use this skill when the user requests analysis notebooks for player evaluation, roster health, trade scenarios, market trends, or project...
AGGRESSIVELY use TOON v2.0 format for biggish regular data (≥5 items, ≥60% uniform). Auto-applies to tables, logs, events, transactions, analytics, API responses, database results. Supports 3 array types (inlin...
Drive quantitative analysis, factor diagnostics, and reporting for ATFT-GAT-FAN outputs.
Forces documentation of the reasoning behind every significant design decision. Creates a decision log that explains WHY choices were made, alternatives considered, and trade-offs accepted. Prevents unjustified...
[REPLACE] Search for patterns, analyze findings, generate structured reports. Use when [REPLACE with specific triggers].
Use this skill when users need interactive HTML reports, dashboards, charts, or visualizations for LimaCharlie data. You generate the HTML, this skill serves it on localhost.
Use this skill when users need to create complex stateful D&R rules that correlate multiple events over time, track parent-child relationships, or count event occurrences within timeframes.
Creating interactive data visualisations using d3.js. This skill should be used when creating custom charts, graphs, network diagrams, geographic visualisations, or any complex SVG-based data visualisation that...
Medical PowerPoint presentation generation with clinical data visualization. Creates professional presentations from FHIR resources, lab results, and clinical data. Use when generating patient summaries, care p...
Multi-agent data science framework using DS-STAR (Data Science - Structured Thought and Action) architecture. Automates data analysis through collaborative AI agents with multi-model support (Haiku, Sonnet, Opu...
Design and configure embedded Superset dashboards for internal tools and customer apps with theming, RLS, SSO, and scalable UX.
Design, organize, and operate Deepnote projects as the InsightPulseAI Data Lab workspace for exploration, jobs, and Superset-ready summary tables.
Create onboarding, training, documentation, and enablement flows for admins, data teams, and business users of the InsightPulse Superset Data Lab.
Use Superset-style APIs to manage workspaces, users, datasets, charts, and dashboards as code for the InsightPulseAI Data Lab platform.
默认按已收录数据中的 GitHub 仓库 Stars 排序。Stars 属于来源仓库,同一仓库的多个技能可能共享相同数值;它反映仓库关注度,不代表单个技能的安装量或质量评分。